09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable electronic publications in the nature of
newsletters in the fields of artificial intelligence
governance, data compliance, data privacy, data security,
and data management. Training services in the fields of artificial intelligence
governance, data compliance, data privacy, data security,
and data management; educational services, namely,
conducting workshops, seminars, conferences,
non-downloadable webinars, multimedia presentations and
trainings in the fields of artificial intelligence
governance, data compliance, data privacy, data security,
and data management. Providing temporary use of on-line non-downloadable software
and applications using artificial intelligence (AI) for data
compliance, data privacy, data security, and data
management; providing temporary use of on-line
non-downloadable software and applications using artificial
intelligence (AI) for analytics-based machine learning, data
automation, data and compliance generation and predictive
analytics being business data analysis in the fields of data
compliance, data privacy, data security, and data
management; providing temporary use of on-line
non-downloadable software and applications using artificial
intelligence (AI) to track compliance and monitor
regulations and laws in the field of artificial intelligence
governance, data compliance, data privacy, data security,
data policy enforcement and data management; software as a
service (SAAS) services featuring software using artificial
intelligence (AI) for data compliance, data privacy, data
security, and data management; software as a service (SAAS)
services featuring software using artificial intelligence
(AI) for analytics-based machine learning, data automation,
data and compliance generation and predictive analytics
being business data analysis in the fields of data
compliance, data privacy, data security, and data
management; software as a service (SAAS) services featuring
software using artificial intelligence (AI) to track
compliance and monitor regulations and laws in the field of
artificial intelligence governance, data compliance, data
privacy, data security, data policy enforcement and data
management; platform as a service (PAAS) services featuring
software using artificial intelligence (AI) for data
compliance, data privacy, data security, and data
management; platform as a service (PAAS) services featuring
software using artificial intelligence (AI) for
analytics-based machine learning, data automation, data and
compliance generation and predictive analytics being
business data analysis in the fields of data compliance,
data privacy, data security, and data management; platform
as a service (PAAS) services featuring software using
artificial intelligence (AI) to track compliance and monitor
regulations and laws in the field of artificial intelligence
governance, data compliance, data privacy, data security,
data policy enforcement and data management; artificial
intelligence as a service (AIAAS) featuring software using
artificial intelligence (AI) for data compliance, data
privacy, data security, and data management; artificial
intelligence as a service (AIAAS) featuring software using
artificial intelligence (AI) for analytics-based machine
learning, data automation, data and compliance generation
and predictive analytics being business data analysis in the
fields of data compliance, data privacy, data security, and
data management; artificial intelligence as a service
(AIAAS) featuring software using artificial intelligence
(AI) to track compliance and monitor regulations and laws in
the field of artificial intelligence governance, data
compliance, data privacy, data security, data policy
enforcement and data management; technological consultancy
in the field of artificial intelligence (AI) technology,
data compliance, data privacy, data security, data policy
enforcement and data management; computer software
consulting.
2.
MODIFYING USER ACCESS LEVELS TO COMPUTING SOFTWARE COMPUTING APPLICATIONS BASED ON DETECTED STATE CHANGES VIA INTEGRATIONS WITH THIRD-PARTY SYSTEMS
Methods, systems, and non-transitory computer readable storage media are disclosed for managing user access levels to computing software applications based on user state changes detected via integration with a third-party system. Specifically, the disclosed system determines a user data object representing a user state associated with a user account in connection with a group of users of an entity by integrating with a third-party user management system. The disclosed system determines application data objects representing computing software applications that correspond to the group of users. Based on the user state, the disclosed system modifies a user access level of the user data object for a computing software application corresponding to the group of users. The disclosed system can generate a request to modify the user access level for providing to an administrator client device or automatically modify the user access level via integration with the third-party user management system.
Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems according to detect and correct configuration gaps with specific system requirements frameworks. Specifically, the disclosed system accesses a digital data repository to determine attribute values of data objects representing functions or infrastructure associated with handling target data for an entity. The disclosed system determines a digital representation of a system requirements framework that indicates controls associated with handling specific data types. Based on the attribute values and a gap rules set associated with the system requirements framework, the disclosed system determines configuration gaps to be addressed via control actions for installing controls in connection with various data assets or data processing operations. The disclosed system generates tasks to display via a graphical user interface of a computing device for applying modifications to the data assets and/or data processing operations to address the configuration gaps.
Methods, systems, and non-transitory computer readable storage media are disclosed for implementation of executing operations with one or more hardware processors to access a tenant database within a multi-tenant environment and generate mapping records for one or more user accounts and one or more objects by executing an eager evaluation model in response to creation of an access policy. The disclosed systems generate policy subject mappings mapping the access policy to user accounts based on attributes of the user account and policy object mappings mapping the access policy to objects according to the attributes of the objects. Upon receiving a request from a user account to access an object within the tenant database, the disclosed systems provide access to the one or more objects based on the policy subject mappings, the policy object mappings, and attributes of the user account.
Methods, systems, and non-transitory computer readable storage media are disclosed for implementation of executing operations with one or more hardware processors to access a tenant database within a multi-tenant environment and generate mapping records for one or more user accounts and one or more objects by executing an eager evaluation model in response to creation of an access policy. The disclosed systems generate policy subject mappings mapping the access policy to user accounts based on attributes of the user account and policy object mappings mapping the access policy to objects according to the attributes of the objects. Upon receiving a request from a user account to access an object within the tenant database, the disclosed systems provide access to the one or more objects based on the policy subject mappings, the policy object mappings, and attributes of the user account.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a decision tree to generate a recommended action in response to detecting a change in a data map representing a computing environment. The disclosed system determines relationships among data objects representing digital data, digital assets, and data processing activities and generates a data map according to the relationships. The disclosed system monitors the data map for changes and, responsive to determining a change in the data map, traverses a decision tree by executing one or more calls to one or more application programming interfaces according to the change in the data map and one or more data policies relevant to the changes. The disclosed systems utilize the decision tree and application programming interfaces to generate a recommended action for modifying digital assets, digital data, and/or data processing activities.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a decision tree to generate a recommended action in response to detecting a change in a data map representing a computing environment. The disclosed system determines relationships among data objects representing digital data, digital assets, and data processing activities and generates a data map according to the relationships. The disclosed system monitors the data map for changes and, responsive to determining a change in the data map, traverses a decision tree by executing one or more calls to one or more application programming interfaces according to the change in the data map and one or more data policies relevant to the changes. The disclosed systems utilize the decision tree and application programming interfaces to generate a recommended action for modifying digital assets, digital data, and/or data processing activities.
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that scan digital applications to intelligently detect potentially insecure data access controls from the digital applications. In particular, the disclosed systems can parse application development libraries to identify potentially insecure data access controls available for utilization within digital applications. Moreover, the disclosed systems can scan an application to detect access controls utilized within the application. Additionally, the disclosed systems can compare the detected, utilized access controls of an application to the potentially insecure data access controls to determine one or more potentially insecure data access controls utilized within the scanned application. In addition, based on detecting one or more potentially insecure data access controls utilized within the scanned application, the disclosed systems can trigger a variety of digital actions within an application scanning platform for the application in response to the one or more potentially insecure data access controls.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
9.
SCANNING DIGITAL APPLICATIONS TO DETECT ACCESS CONTROL SECURITY RISKS
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that scan digital applications to intelligently detect potentially insecure data access controls from the digital applications. In particular, the disclosed systems can parse application development libraries to identify potentially insecure data access controls available for utilization within digital applications. Moreover, the disclosed systems can scan an application to detect access controls utilized within the application. Additionally, the disclosed systems can compare tire detected, utilized access controls of an application to the potentially insecure data access controls to determine one or more potentially insecure data access controls utilized within the scanned application. In addition, based on detecting one or more potentially insecure data access controls utilized within the scanned application, the disclosed systems can trigger a variety of digital actions within an application scanning platform for the application in response to the one or more potentially insecure data access controls.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that utilize a repository of metadata-based recommendations to classify data sources using metadata from the data sources. For example, the disclosed systems can generate a repository of metadata-based recommendations that indicate recommended classifications for objects within data sources through metadata associated with a data source schema. In some instances, the disclosed systems identify metadata from a data source schema associated with the data source. Subsequently, the disclosed systems can match the identified metadata to a metadata-based recommendation via metadata mappings in the metadata-based recommendation repository to select a metadata-based recommendation. Furthermore, the disclosed systems can also utilize a classifier model to generate predicted labels for the data source and update the metadata-based recommendation repository with a mapping between the predicted labels and metadata corresponding to the data source schema of the data source.
In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for mapping the existence of target data within computing systems in a manner that does not expose the target data to potential data-related incidents. In accordance with various aspects, a method is provided that comprises: receiving a source dataset that comprises a label assigned to a data element used by a data source in handling target data that identifies a type of target data and data samples gathered for the data element; determining, based on the label, that the data samples are to be anonymized; generating supplemental anonymizing data samples associated with the label that comprise fictitious occurrences of the type of the target data; generating a review dataset comprising the supplemental anonymizing data samples intermingled with the data samples; and sending the review dataset to a review computing system.
Methods, systems, and non-transitory computer readable storage media are disclosed for updating the priority of classifiers in a classifier model. Specifically, the disclosed systems execute operations to extract data elements from a digital dataset. The disclosed system generates first classifier labels for a first subset of data elements (e.g., a test dataset) by utilizing a classification model to apply a predetermined order of classifiers to the first subset of data elements. The disclosed systems utilize the first classifier labels to determine a priority order for the classifiers for applying to a second subset of data elements the digital dataset. Using the determined priority order of the classifiers, the disclosed systems can generate second classifier labels for a second subset of data elements by utilizing the classifier model to apply the classifiers according to the priority order.
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Downloadable electronic publications in the nature of newsletters and ebooks in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Digital media, namely, downloadable webcasts, podcasts, and multimedia files containing audio and video recordings in the fields of AI governance, privacy, consent, ethics, compliance, data, risk, and workplace culture; Downloadable chatbot software using artificial intelligence (AI) for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Downloadable software in the nature of a mobile application for managing, organizing, and facilitating events, conferences, and meetings in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Downloadable software development kits (SDK); Downloadable application programming interface (API) software Business consulting services in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Providing business information in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management Training services in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Educational services, namely, conducting workshops, seminars, conferences, non-downloadable webinars, multimedia presentations and trainings in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Providing a website featuring blogs and non-downloadable publications in the nature of articles in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Online publication of blogs, letters, newsletters, articles, news stories, and fact sheets in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Providing a non-downloadable multimedia program series featuring content about AI governance, privacy, consent, ethics, compliance, data, risk, and workplace culture via a video-on-demand service; Entertainment services, namely, providing podcasts and webcasts in the fields of AI governance, privacy, consent, ethics, compliance, data, risk, and workplace culture Providing temporary use of on-line non-downloadable software and applications using artificial intelligence for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; providing temporary use of on-line non-downloadable software and applications using artificial intelligence for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; providing temporary use of on-line non-downloadable software and applications using artificial intelligence to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; software as a service (SAAS) services featuring software using artificial intelligence for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; software as a service (SAAS) services featuring software using artificial intelligence for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; software as a service (SAAS) services featuring software using artificial intelligence to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; platform as a service (PAAS) services featuring software using artificial intelligence for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; platform as a service (PAAS) services featuring software using artificial intelligence for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; platform as a service (PAAS) services featuring software using artificial intelligence to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; consultancy in the field of regulatory compliance, artificial intelligence governance and technology, risk management, data privacy, data security, data policy enforcement, and data management; computer software consulting; Providing temporary use of online non-downloadable software and applications for managing user consent, cookies, and privacy preferences; Software as a service (SAAS) services for managing user consent, cookies, and privacy preferences; Technology consultation in the field of cybersecurity; Data encryption services; Providing an online database featuring regulatory information in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Application service provider featuring application programming interface (API) software; Providing temporary use of online non-downloadable software using artificial intelligence (AI) for automating workflows, record-keeping, reporting, and notification guidance; Providing temporary use of online non-downloadable chatbot software using artificial intelligence (AI) for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management Consulting services in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; Providing regulatory compliance information in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Advisory consulting services relating to regulatory compliance matters in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management
09 - Appareils et instruments scientifiques et électriques
35 - Publicité; Affaires commerciales
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Downloadable electronic publications in the nature of newsletters and ebooks in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Digital media, namely, downloadable webcasts, podcasts, and multimedia files containing audio and video recordings in the fields of AI governance, privacy, consent, ethics, compliance, data, risk, and workplace culture; Downloadable chatbot software using artificial intelligence (AI) for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Downloadable software in the nature of a mobile application for managing, organizing, and facilitating events, conferences, and meetings in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Downloadable software development kits (SDK); Downloadable application programming interface (API) software Business consulting services in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Providing business information in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management Training services in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Educational services, namely, conducting workshops, seminars, conferences, non-downloadable webinars, multimedia presentations and trainings in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Providing a website featuring blogs and non-downloadable publications in the nature of articles in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Online publication of blogs, letters, newsletters, articles, news stories, and fact sheets in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Providing a non-downloadable multimedia program series featuring content about AI governance, privacy, consent, ethics, compliance, data, risk, and workplace culture via a video-on-demand service; Entertainment services, namely, providing podcasts and webcasts in the fields of AI governance, privacy, consent, ethics, compliance, data, risk, and workplace culture Providing temporary use of on-line non-downloadable software and applications using artificial intelligence for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; providing temporary use of on-line non-downloadable software and applications using artificial intelligence for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; providing temporary use of on-line non-downloadable software and applications using artificial intelligence to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; software as a service (SAAS) services featuring software using artificial intelligence for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; software as a service (SAAS) services featuring software using artificial intelligence for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; software as a service (SAAS) services featuring software using artificial intelligence to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; platform as a service (PAAS) services featuring software using artificial intelligence for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; platform as a service (PAAS) services featuring software using artificial intelligence for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; platform as a service (PAAS) services featuring software using artificial intelligence to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) to track compliance and monitor regulations and laws in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; consultancy in the field of regulatory compliance, artificial intelligence governance and technology, risk management, data privacy, data security, data policy enforcement, and data management; computer software consulting; Providing temporary use of online non-downloadable software and applications for managing user consent, cookies, and privacy preferences; Software as a service (SAAS) services for managing user consent, cookies, and privacy preferences; Technology consultation in the field of cybersecurity; Data encryption services; Providing an online database featuring regulatory information in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Application service provider featuring application programming interface (API) software; Providing temporary use of online non-downloadable software using artificial intelligence (AI) for automating workflows, record-keeping, reporting, and notification guidance; Providing temporary use of online non-downloadable chatbot software using artificial intelligence (AI) for regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management Consulting services in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, data policy enforcement, and data management; Providing regulatory compliance information in the field of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management; Advisory consulting services relating to regulatory compliance matters in the fields of regulatory compliance, artificial intelligence governance, risk management, data privacy, data security, and data management
15.
GENERATING GRAPH-BASED TAXONOMIES VIA GRAPHICAL USER INTERFACE TOOLS FOR GENERATING REPRESENTATIVE DATA OBJECTS AND CUSTOMIZING ATTRIBUTES
Methods, systems, and non-transitory computer readable storage media are disclosed for dynamically generating and modifying interactive graph-based taxonomies associated with data processes in various domains. The disclosed system generates node data objects representing a domain-category hierarchy in connection with one or more computing data processes via a library of tools. The disclosed systems generates an attribute data object corresponding to an attribute assigned to a node data object in the graph-based taxonomy and links the attribute data object to node data objects according to parent/child relationships of the hierarchy. The disclosed system utilizes the parent/child relationships of the node data objects and attribute data object to aggregate attribute values of the attributes according to one or more aggregation operations. The disclosed systems provide indications of the aggregated attribute values for display via a graphical user interface for use in performing data processes.
Embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for permitting or blocking tracking tools used through webpages. In particular embodiments, the method involves: scanning a webpage to identify a tracking tool configured for processing personal data; determining a data destination location that is associated with the tracking tool; and generating program code configured to: determine a location associated with a user who is associated with a rendering of the webpage; determine a prohibited data destination location based on the location associated with the user; determine that the data destination location associated with the tracking tool is not the prohibited data destination location; and responsive to the data destination location associated with the tracking tool not being the prohibited data destination location, permit the tracking tool to execute.
In various embodiments, a data map generation system is configured to receive a request to generate a privacy-related data map for particular computer code, and, at least partially in response to the request, determine a location of the particular computer code, automatically obtain the particular computer code based on the determined location, and analyze the particular computer code to determine privacy-related attributes of the particular computer code, where the privacy-related attributes indicate types of personal information that the particular computer code collects or accesses. The system may be further configured to generate and display a data map of the privacy-related attributes to a user.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
18.
CAPTURING AND CATEGORIZING NETWORK TRAFFIC DATA FROM API PAYLOADS FOR COMPREHENSIVE RISK SCANNING
Methods, systems, and non-transitory computer readable storage media are disclosed for capturing, analyzing, and classifying network traffic data associated with a network communication between computing systems. For example, the disclosed systems execute operations to generate classifications of the content of the network traffic data utilizing a classification model. For example, the disclosed systems determine risk levels based on whether network traffic data transmitted within the transport layer of the network traffic data adheres to the requirements of the data policy. In certain aspects, the disclosed systems analyze captured network traffic data based a live network transmissions, logged network transmissions, an API specification, and/or API endpoints. In some aspects, the disclosed systems provide a classification analysis including risk levels associated with the network traffic data via a custom graphical user interface.
G06F 21/50 - Contrôle des utilisateurs, des programmes ou des dispositifs de préservation de l’intégrité des plates-formes, p. ex. des processeurs, des micrologiciels ou des systèmes d’exploitation
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
Methods, systems, and non-transitory computer readable storage media are disclosed for capturing, analyzing, and classifying network traffic data associated with a network communication between computing systems. For example, the disclosed systems execute operations to generate classifications of the content of the network traffic data utilizing a classification model. For example, the disclosed systems determine risk levels based on whether network traffic data transmitted within the transport layer of the network traffic data adheres to the requirements of the data policy. In certain aspects, the disclosed systems analyze captured network traffic data based a live network transmissions, logged network transmissions, an API specification, and/or API endpoints. In some aspects, the disclosed systems provide a classification analysis including risk levels associated with the network traffic data via a custom graphical user interface.
H04L 43/045 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux pour la visualisation graphique des données de surveillance
Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems to classify and modify digital content items to satisfy digital data requirements of data policies. For example, the content classification system validates, enforces, and remediates digital data content corresponding to digital data requirements of a data policy based on data types covered by the data policy. The disclosed systems generate classifications for digital content items by accessing digital content items and generating mappings between the digital content items and a data policy. The disclosed systems utilize the mappings and digital data requirements of the data policy to determine whether the digital content items violate one or more elements of the data policy. The disclosed systems can perform various downstream operations to remediate the data policy violations, such as by causing various computing devices to modify the violating digital content items.
Methods, systems, and non-transitory computer readable storage media are disclosed for detecting missing data in a digital data repository according to a set of digital data requirements and extracted data attributes for correcting database operations. The disclosed system utilizes a classifier model to classify digital content items via an integration with the digital data repository. The disclosed system generates mappings indicating that the digital content items correspond to digital data requirements of a data policy based on the classifications. The disclosed system utilizes the mappings to determine that one or more types of data are missing from the digital data repository as indicated by the digital data requirements. The disclosed system generate an indication of the data missing from the digital data repository for use in performing additional operations, such as modifying a database operation having access to the digital content items to prevent further errors.
Methods, systems, and non-transitory computer readable storage media are disclosed for correcting entity detection errors with entity correction and resolution in optical character recognition for digitization of physical documents. Specifically, the disclosed system utilizes named entity recognition to extract entities from character strings (e.g., words) in a digital text document. The disclosed system also tokenizes the character strings in the digital text document based on attributes of the character strings. Furthermore, the disclosed system compares the extracted entities and tokenized character strings to determine similarity metrics between the extracted entities and tokenized character strings. The disclosed system also compares extracted entities to character strings including special/numerical characters to determine similarity metrics indicating correlation probabilities between entities and character strings. The disclosed systems generate mappings between the tokens and entities based on the similarity metrics to resolve entities to likely corresponding character strings while correcting for errors during entity extraction.
Methods, systems, and non-transitory computer readable storage media are disclosed for optimizing computer memory usage for lookup lists in computer memory via probabilistic data structures. For example, the disclosed system generates a probabilistic data structure (e.g., a Bloom filter) to represent data in a lookup list including multi-token items by hashing items of the lookup list to sets of bit values in a bit vector. The disclosed system classifies text content in a digital document by utilizing a maximum number of tokens from multi-token items in the lookup list to select and compare sets of sequential tokens in the digital document to the probabilistic data structure. The disclosed system also iteratively reduces the number of tokens in sets of sequential tokens for subsequent comparisons. Furthermore, in some aspects, the disclosed system causes a computing device to modify a digital document and/or database operations based on the classifications.
Methods, systems, and non-transitory computer readable storage media are disclosed for controlling access to artificial intelligence systems based on determined intent of queries. The disclosed system utilizes one or more digital content analysis models to determine an intent of one or more queries to an artificial intelligence system. The disclosed system utilizes the one or more digital content analysis models to determine an intended use of the artificial intelligence system. Additionally, the disclosed system determines whether the intent of the one or more queries aligns with the intended use of the artificial intelligence system by generating a similarity score and comparing the similarity score to a similarity threshold. Based on whether the intent aligns with the intended use, the disclosed system executes computing instructions to enable or block the one or more queries from being processed by the artificial intelligence system.
Methods, systems, and non-transitory computer readable storage media are disclosed for controlling access to artificial intelligence systems based on determined intent of queries. The disclosed system utilizes one or more digital content analysis models to determine an intent of one or more queries to an artificial intelligence system. The disclosed system utilizes the one or more digital content analysis models to determine an intended use of the artificial intelligence system. Additionally, the disclosed system determines whether the intent of the one or more queries aligns with the intended use of the artificial intelligence system by generating a similarity score and comparing the similarity score to a similarity threshold. Based on whether the intent aligns with the intended use, the disclosed system executes computing instructions to enable or block the one or more queries from being processed by the artificial intelligence system.
Methods, systems, and non-transitory computer readable storage media are disclosed for routing digital content items to priority-based processing queues based on classifications of the digital content items according to one or more system requirements frameworks. Specifically, the disclosed system scans and classifies digital content items at a digital data repository based on data types included in the digital content items. The disclosed system utilizes a classification model with a classification profile to classify the digital content items according to one or more system requirements frameworks and routes the digital content items to priority-based processing queues according to priority levels indicated by the classifications. Furthermore, the disclosed system provides indications of classifications of the portions of the digital content items (e.g., to indicate high priority data). The disclosed system can also perform additional computing operations on the digital content items according to the routing via the priority-based processing queues.
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that scans application codes to detect data processing activity components utilized a type-based analysis. For example, the disclosed systems can extract data type information from input application code and utilize the data type information to identify a list of potential (or candidate) function call components for the particular extracted data type. In addition, the disclosed systems can utilize a pattern matching model to match the list of potential function call components to function call component signatures within the application code. Moreover, the disclosed systems can utilize the determined function call component signatures with a detector specification to identify particular data processing activity components (e.g., SDKs, targets, method calls) corresponding to the application code. Moreover, the disclosed systems can display the identified data processing activity components within a software profile for the application code.
G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
28.
SCANNING APPLICATION CODE TO DETECT AND CLASSIFY SDK DATA UTILIZING A TYPE-BASED ANALYSIS
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that scans application codes to detect data processing activity components utilized a type-based analysis. For example, the disclosed systems can extract data type information from input application code and utilize the data type information to identify a list of potential (or candidate) function call components for the particular extracted data type. In addition, the disclosed systems can utilize a pattern matching model to match the list of potential function call components to function call component signatures within the application code. Moreover, the disclosed systems can utilize the determined function call component signatures with a detector specification to identify particular data processing activity components (e.g., SDKs, targets, method calls) corresponding to the application code. Moreover, the disclosed systems can display the identified data processing activity components within a software profile for the application code.
G06F 8/75 - Analyse structurelle pour la compréhension des programmes
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 8/74 - Ingénierie inverseExtraction d’informations sur la conception à partir du code source
Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems to comply with system requirements frameworks that indicate specific requirements on how the computing systems should handle certain data types. In response to detecting a change to one or more digital data requirements of a system requirements framework, the disclosed systems access a configuration profile of an entity and utilize a large language model to determine if data assets or data processing operations comply with the changes to the digital data requirements. In response to determining a configuration gap of the configuration profile based on detected changes to the digital data requirements, the disclosed systems utilize a large language model to generate tasks for correcting the configuration gap. The disclosed systems generate one or more tasks by modifying data assets, data processing operations, or other digital data associated with the entity.
Methods, systems, and non-transitory computer readable storage media are disclosed for facilitating digital report generation across separate software computing applications via application and digital data extraction integration. The disclosed system utilizes integrated software computing applications to perform cross-application tasks to generate and edit digital reports. The disclosed system provides tools within a data management software application to create a digital report from data objects generated from data extracted from digital data repositories associated with an entity. In response to a request via the data management software application, the disclosed system performs operations to launch a digital content editing application displaying a digital report template including the data represented by the data objects. In response to launching the digital content editing application, the disclosed system causes the digital content editing application to open a panel with tools corresponding to the data management software application for editing the digital report template.
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 40/103 - Mise en forme, c.-à-d. modification de l’apparence des documents
G06V 30/416 - Extraction de la structure logique, p. ex. chapitres, sections ou numéros de pageIdentification des éléments de document, p. ex. des auteurs
G06V 30/42 - Reconnaissance des formes à partir d’images axée sur les documents basées sur le type de document
32.
Data processing systems and methods for automatically detecting and documenting privacy-related aspects of computer software
Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating multidimensional risk visualizations depicting severity and frequency and for predicting risk mitigation strategies. For R example, the disclosed systems generate multidimensional risk visualizations that present visual representations of risk severity and risk frequency in multidimensional formats, including many risk dimensions at once. In certain cases, the disclosed systems further utilize a particular machine learning model such as a strategy prediction neural network to generate predicted mitigation strategies based on risk data.
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
G06Q 10/067 - Modélisation d’entreprise ou d’organisation
34.
DATA PROCESSING SYSTEMS AND METHODS FOR INTEGRATING PRIVACY INFORMATION MANAGEMENT SYSTEMS WITH DATA LOSS PREVENTION TOOLS OR OTHER TOOLS FOR PRIVACY DESIGN
Computer implemented methods, according to various embodiments, comprise: (1) integrating a privacy management system with DLP tools; (2) using the DLP tools to identify sensitive information that is stored in computer memory outside of the context of the privacy management system; and (3) in response to the sensitive data being discovered by the DLP tool, displaying each area of sensitive data to a privacy officer (e.g., similar to pending transactions in a checking account that have not been reconciled). A designated privacy officer may then select a particular entry and either match it up (e.g., reconcile it) with an existing data flow or campaign in the privacy management system, or trigger a new privacy assessment to be done on the data to capture the related privacy attributes and data flow information.
In general, various aspects provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for performing data discovery on a target computing system. In various aspects, a third party computing connects, via a public data network, to an edge node of the target computing system and instructs the target computing system to execute jobs to discover target data stored in data repositories in a private data network in the target computing system. In some aspects, the third party computing system may schedule the jobs on the target computing system based on computing resource availability on the target computing system.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
G06Q 10/063 - Recherche, analyse ou gestion opérationnelles
36.
SYSTEMS AND METHODS FOR DETECTING PREJUDICE BIAS IN MACHINE-LEARNING MODELS
Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for detecting prejudice bias in machine-learning models and/or data sets used in training, testing, and/or validating the models. In accordance various aspects, a method is provided comprising: receiving a data set used for training, testing, and/or validating a model that comprises data instances; generating, using a classification model, a prediction of applicability for each sub-category of a plurality of sub-categories for each bias category of a plurality of bias categories for each data instance; determining that a particular sub-category for a particular bias category is applicable to a proportion of the data set, wherein predictions of applicability for the particular sub-category generated for the proportion of the data set satisfies a threshold; and determining, based on the proportion, that the data set has a prejudice bias with respect to the particular bias category.
41 - Éducation, divertissements, activités sportives et culturelles
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Training services in the fields of artificial intelligence governance, data compliance, data privacy, data security, and data management; educational services, namely, conducting workshops, seminars, conferences, non-downloadable webinars, multimedia presentations and trainings in the fields of artificial intelligence governance, data compliance, data privacy, data security, and data management Providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for data compliance, data privacy, data security, and data management; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of data compliance, data privacy, data security, and data management; providing temporary use of on-line non-downloadable software and applications using artificial intelligence (AI) to track compliance and monitor regulations and laws in the field of artificial intelligence governance, data compliance, data privacy, data security, data policy enforcement and data management; software as a service (SAAS) services featuring software using artificial intelligence (AI) for data compliance, data privacy, data security, and data management; software as a service (SAAS) services featuring software using artificial intelligence (AI) for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of data compliance, data privacy, data security, and data management; software as a service (SAAS) services featuring software using artificial intelligence (AI) to track compliance and monitor regulations and laws in the field of artificial intelligence governance, data compliance, data privacy, data security, data policy enforcement and data management; platform as a service (PAAS) services featuring software using artificial intelligence (AI) for data compliance, data privacy, data security, and data management; platform as a service (PAAS) services featuring software using artificial intelligence (AI) for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of data compliance, data privacy, data security, and data management; platform as a service (PAAS) services featuring software using artificial intelligence (AI) to track compliance and monitor regulations and laws in the field of artificial intelligence governance, data compliance, data privacy, data security, data policy enforcement and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) for data compliance, data privacy, data security, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) for analytics-based machine learning, data automation, data and compliance generation and predictive analytics being business data analysis in the fields of data compliance, data privacy, data security, and data management; artificial intelligence as a service (AIAAS) featuring software using artificial intelligence (AI) to track compliance and monitor regulations and laws in the field of artificial intelligence governance, data compliance, data privacy, data security, data policy enforcement and data management; consultancy in the field of artificial intelligence (AI) technology, data compliance, data privacy, data security, data policy enforcement and data management; computer software consulting
Various embodiments provide methods, apparatus, systems, computing devices, computing entities, and/or the like for identifying targeted data for a data subject across a plurality of data objects in a data source. In accordance with one embodiment, a method is provided comprising: receiving a request to identify targeted data for a data subject; identifying a first data object using metadata for a data source that identifies the first data object as associated with a first targeted data type for a data portion from the request; identifying a first data field from a graph data structure of the first data object that identifies the first data field as used for storing data having the first targeted data type; and querying the first data object based on the first data field and the data for the first targeted data type to identify a first targeted data portion for the data subject.
Methods, systems, and non-transitory computer readable storage media are disclosed for facilitating modification of components of artificial intelligence computing applications via aggregated risk scores of individual artificial intelligence computing application components. The disclosed system generates data objects representing the artificial intelligence computing application components. The disclosed system determines mappings between the data objects based on relationships of the artificial intelligence computing application components. Furthermore, the disclosed system generates risk scores for the data objects representing the components of the artificial intelligence computing application by administering risk assessments that correspond to a system requirements framework. The disclosed system also generates an interactive aggregated risk indicator indicating contributions of the components to the artificial intelligence computing application in relation to the system requirements framework by combining the risk scores of the data objects according to the mappings between the data objects.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
40.
DATA PROCESSING SYSTEMS AND METHODS FOR SYNCHING PRIVACY-RELATED USER CONSENT ACROSS MULTIPLE COMPUTING DEVICES
A privacy-related consent extension and data processing system may be configured to automatically extend one or more privacy-related consents for a user of a first computing device to a second computing device. In various embodiments, the system is configured to provide a computer-readable indicium (indicia) on a previously unknown computing device upon initiation of a transaction between a user and an entity collecting and processing privacy data. In response to a user using a known computing device to scan the computer-readable indicium, in various embodiments, the system may provide the ability to share user consent data provided by the first known device to the second unknown device, allowing the user to provide consent without manually re-entering privacy and consent preferences.
Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems to classify and modify digital content items to satisfy digital data requirements of data policies. For example, the content classification system validates, enforces, and remediates digital data content corresponding to digital data requirements of a data policy based on data types covered by the data policy. The disclosed systems generate classifications for digital content items by accessing digital content items and generating mappings between the digital content items and a data policy. The disclosed systems utilize the mappings and digital data requirements of the data policy to determine whether the digital content items violate one or more elements of the data policy. The disclosed systems can perform various downstream operations to remediate the data policy violations, such as by causing various computing devices to modify the violating digital content items.
Embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for verifying the identity of a data subject. In one embodiment, a method is provided comprising: receiving, via a browser, a consumer rights request for a data subject for performing an action with regard to personal data associated with the data subject; detecting a state of the browser indicating a location; identifying a law based on the location; determining a level of identity verification required based on the law; generating, based on the level, a GUI by configuring a first prompt on the GUI configured for receiving input for a first type of identity verification; transmitting an instruction to present the GUI; receiving the input for the first type of identity verification; verifying the identity of the data subject based on the input; and responsive to verifying the identity, causing performance of the action.
Methods, systems, and non-transitory computer readable storage media are disclosed for dynamically generating and modifying interactive graph-based taxonomies associated with data processes in various domains. The disclosed system generates node data objects representing a domain-category hierarchy in connection with one or more computing data processes via a library of tools. The disclosed systems generates an attribute data object corresponding to an attribute assigned to a node data object in the graph-based taxonomy and links the attribute data object to node data objects according to parent/child relationships of the hierarchy. The disclosed system utilizes the parent/child relationships of the node data objects and attribute data object to aggregate attribute values of the attributes according to one or more aggregation operations. The disclosed systems provide indications of the aggregated attribute values for display via a graphical user interface for use in performing data processes.
Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for implementing and managing access to particular data based on access controls for implementing purpose restrictions and/or consent restrictions. In various aspects, a method is provided that comprises: receiving a request transmitted by an application executing on a client computing system and requesting access to a dataset, wherein each data record of the dataset comprises data elements; identifying, based on the application, a purpose for the application requesting access to the dataset; referencing, based on the purpose, an applicable purpose-based access-control policy to identify an authorization token; and providing the authorization token, wherein the storage computing system provides the client computing system with a view of the dataset based on the token with the view having a data element returning modified data in a manner compliant with the applicable purpose-based access-control policy.
Methods, systems, and non-transitory computer readable storage media are disclosed for detecting missing data in a digital data repository according to a set of digital data requirements and extracted data attributes for correcting database operations. The disclosed system utilizes a classifier model to classify digital content items via an integration with the digital data repository. The disclosed system generates mappings indicating that the digital content items correspond to digital data requirements of a data policy based on the classifications. The disclosed system utilizes the mappings to determine that one or more types of data are missing from the digital data repository as indicated by the digital data requirements. The disclosed system generate an indication of the data missing from the digital data repository for use in performing additional operations, such as modifying a database operation having access to the digital content items to prevent further errors.
Methods, systems, and non-transitory computer readable storage media are disclosed for optimizing computer memory usage for lookup lists in computer memory via probabilistic data structures. For example, the disclosed system generates a probabilistic data structure (e.g., a Bloom filter) to represent data in a lookup list including multi-token items by hashing items of the lookup list to sets of bit values in a bit vector. The disclosed system classifies text content in a digital document by utilizing a maximum number of tokens from multi-token items in the lookup list to select and compare sets of sequential tokens in the digital document to the probabilistic data structure. The disclosed system also iteratively reduces the number of tokens in sets of sequential tokens for subsequent comparisons. Furthermore, in some aspects, the disclosed system causes a computing device to modify a digital document and/or database operations based on the classifications.
Techniques are disclosed for usage-tracking of various information security (InfoSec) entities for tenants/organization onboarded on an instant multi-tenant security assurance platform. The InfoSec entities include policies, procedures, controls and evidence tasks. A policy or procedure is enforced by implementing one or more controls, and the collection of one or more evidence tasks proves/verifies the implementation of a control. The InfoSec entities are linked to each other across the platform and accrue a number of benefits for the tenants. These include generating a security questionnaire response (SQR), defining a readiness project and an audit project, sharing InfoSec entities encompassing the various products of a tenant, automating risk assessment, automatic collection of evidence tasks for verifying the implementation and/or operational state/status of various mitigating controls, etc.
In various embodiments, an entity may provide a WebView where a transaction between an entity and a data subject may be performed. As described herein, the transaction may involve the collection or processing of personal data associated with the data subject by the entity as part of a processing activity undertaken by the entity that the data subject is consenting to as part of the transaction. Additionally, the entity may provide a native application where the transactions between the entity and a data subject may be performed. In some embodiments, the system may be configured to share consent data between the WebView and the native application so data subjects experience a seamless transition while using either the WebView or the native application, and the data subjects are not required to go through a consent workflow for each of the WebView and the native application.
Various aspects of the disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for facilitating the exchange of data among a diverse group of first and third party computing environments. Accordingly, various aspects of the disclosure provide a data exchange computing platform that facilitates data exchange among a diverse group of first and third party computing environments. In some aspects, the data exchange computing platform provides a data exchange service available to various first and third parties who wish to exchange data.
Various aspects of the disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for facilitating the exchange of data among a diverse group of first and third party computing environments. Accordingly, various aspects of the disclosure provide a data exchange computing platform that facilitates data exchange among a diverse group of first and third party computing environments. In some aspects, the data exchange computing platform provides a data exchange service available to various first and third parties who wish to exchange data.
Various aspects of the disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for facilitating the exchange of data among a diverse group of first and third party computing environments. Accordingly, various aspects of the disclosure provide a data exchange computing platform that facilitates data exchange among a diverse group of first and third party computing environments. In some aspects, the data exchange computing platform provides a data exchange service available to various first and third parties who wish to exchange data.
Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing machine-learning models to deduplicate electronic survey questions of electronic surveys or questionnaires in real-time. Specifically, the disclosed system maps electronic survey questions to specific domain classifications by utilizing a machine-learning model to classify portions of electronic surveys based on context within the portions of the electronic surveys. Additionally, the disclosed system utilizes the mappings of electronic survey questions to domain classifications to determine whether to deduplicate specific questions that are semantically similar and within the same domain classifications. For instance, the disclosed system utilizes natural language processing to find semantically similar questions across a plurality of electronic surveys and deduplicate the similar questions if their domain classifications are the same.
In various embodiments, a system may be configured to substantially automatically determine whether to take one or more actions in response to one or more identified risk triggers (e.g., data breaches, regulation change, etc.). The system may, for example: (1) compare the potential risk trigger to one or more previous risks triggers experienced by the particular entity at a previous time; (2) identify a similar previous risk trigger (e.g., one or more previous risk triggers related to a similar change in regulation, breach of data, type of issue identified, etc.); (3) determine the relevance of the current risk trigger based at least in part on a determined relevance of the previous risk trigger; and (4) determine whether to take one or more actions to the current risk trigger based at least in part on one or more determined actions to take in response to the previous, similar risk trigger.
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06Q 10/067 - Modélisation d’entreprise ou d’organisation
54.
Modifying control scopes of controls across a plurality of data processes via data objects
Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems according to detect and correct configuration gaps with specific system requirements frameworks. Specifically, the disclosed system accesses a digital data repository to determine attribute values of data objects representing functions or infrastructure associated with handling target data for an entity. The disclosed system determines a digital representation of a system requirements framework that indicates controls associated with handling specific data types. Based on the attribute values and a gap rules set associated with the system requirements framework, the disclosed system determines configuration gaps to be addressed via control actions for installing controls in connection with various data assets or data processes. The disclosed system generates tasks to display via a graphical user interface of a computing device for applying modifications to the data assets and/or data processes to address the configuration gaps.
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for auto-blocking of software development kit functionality for mobile software applications based on consent (or lack thereof) provided by users who are interacting with the mobile software applications.
In various aspects, a data transfer discovery and analysis system may query an entity computing system to identify access credentials for third-party computing systems and scan each access credential to determine associated permissions provided by each access credential on the entity computing system. The data transfer discovery and analysis system may further inspect access logs to identify actual data transfers between the entity computing system and third-party computing systems as well as other access activity associated with each of the credentials. The system can generate and store a mapping of all actual data transfers (e.g., based on the access log data) and potential data transfers (e.g., based on particular access permissions) between/among the entity computing system and the third-party computing systems. By analyzing access logs to determine actual data transfers executed under each particular access credential, the data transfer discovery and analysis system can identify unused and/or underutilized access permissions.
Methods, systems, and non-transitory computer readable storage media are disclosed for managing user access levels to computing software applications based on user state changes detected via integration with a third-party system. Specifically, the disclosed system determines a user data object representing a user state associated with a user account in connection with a group of users of an entity by integrating with a third-party user management system. The disclosed system determines application data objects representing computing software applications that correspond to the group of users. Based on the user state, the disclosed system modifies a user access level of the user data object for a computing software application corresponding to the group of users. The disclosed system can generate a request to modify the user access level for providing to an administrator client device or automatically modify the user access level via integration with the third-party user management system.
Methods, systems, and non-transitory computer readable storage media are disclosed for determining clusters of similar digital documents using unique document signatures. Specifically, the disclosed system processes digital text in a digital document to tokenize character strings (e.g., words) in the digital document by combining a subset of character values and string lengths in the character strings. Additionally, the disclosed system generates a document signature for the digital document by combining subsets of tokens generated for the digital document into a token sequence indicative of the digital text in the digital document. The disclosed system determines a cluster of similar digital documents including the digital document by comparing the document signature of the digital document to document signatures corresponding to a plurality of digital documents.
The present disclosure provides methods, apparatus, systems, computing devices, computing entities, and/or the like for providing persistent representations in graph data structures of relationships that exist among data objects found across different data-related processes to enable efficient querying of data from the different data-related processes.
41 - Éducation, divertissements, activités sportives et culturelles
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
(Based on Use in Commerce) Arranging and conducting workshops, seminars, and training in the field of artificial intelligence governance; Educational training of others in the field of artificial intelligence governance; (Based on Intent To Use) ; Arranging and conducting conferences, non-downloadable webinars, and multimedia presentations in the field of artificial intelligence governance; Providing a website featuring blogs and non-downloadable publications in the nature of articles in the field of artificial intelligence governance; Online publication of blogs, letters, newsletters, articles, news stories, and fact sheets in the fields of artificial intelligence governance Providing information in the field of artificial intelligence governance law; Providing information in the field of artificial intelligence governance law via a website
62.
Data processing systems and methods for automatically blocking the use of tracking tools
Data processing systems and methods, according to various embodiments, are adapted for determining a categorization for each tracking tool that executes on a particular webpage based on a variety of criteria, such as the purpose of the tracking tool and its source script. The system may compare the characteristics of tracking tools on a webpage to a database of known tracking tools to determine the appropriate categorization. When a user visits the webpage, the system analyzes these categories and determines whether the tracking tool should be permitted to run based on the categories and/or other criteria, such as whether the user has consented to the use of that type of tracking tool.
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Professional business networking services; promoting the exchange of information and resources concerning corporate compliance, corporate ethics, and workplace misconduct; promoting public awareness of developments in the fields of corporate compliance, corporate ethics, and workplace misconduct. Arranging and conducting workshops, seminars, conferences, non-downloadable webinars, multimedia presentations and trainings in the fields of corporate compliance, corporate ethics, and workplace misconduct; Educational training of others in the fields of corporate compliance, corporate ethics, and workplace misconduct; Providing a website featuring blogs and non-downloadable publications in the nature of articles in the fields of corporate compliance, corporate ethics, and workplace misconduct; Online publication of blogs, letters, newsletters, articles, news stories, and fact sheets in the fields of corporate compliance, corporate ethics, and workplace misconduct.
64.
METHODS AND GRAPHICAL USER INTERFACES FOR SCANNING APPLICATION CODE TO DETECT AND CLASSIFY SDK DATA INTO DATA CATEGORIES
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that generate insightful user interfaces that display data processing activity components from the application codes, data categories for the detected components, and/or modifications of data categories and/or data processing activity components. For example, the disclosed system can utilize the application code scan to categorize one or more data types and/or data processing purposes represented by the various detected data processing activity components. Additionally, the disclosed systems can generate dynamic graphical user interfaces with the data processing activity components and data categories to enable quick and insightful access to a wide breadth of information from an application code scan. Moreover, the disclosed systems can also determine (and display) changes of data processing activity components and/or data categories detected between scans of different versions of the application code.
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that generate insightful user interfaces that display data processing activity components from the application codes, data categories for the detected components, and/or modifications of data categories and/or data processing activity components. For example, the disclosed system can utilize the application code scan to categorize one or more data types and/or data processing purposes represented by the various detected data processing activity components. Additionally, the disclosed systems can generate dynamic graphical user interfaces with the data processing activity components and data categories to enable quick and insightful access to a wide breadth of information from an application code scan. Moreover, the disclosed systems can also determine (and display) changes of data processing activity components and/or data categories detected between scans of different versions of the application code.
Embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for permitting or blocking tracking tools used through webpages. In particular embodiments, the method involves: scanning a webpage to identify a tracking tool configured for processing personal data; determining a data destination location that is associated with the tracking tool; and generating program code configured to: determine a location associated with a user who is associated with a rendering of the webpage; determine a prohibited data destination location based on the location associated with the user; determine that the data destination location associated with the tracking tool is not the prohibited data destination location; and responsive to the data destination location associated with the tracking tool not being the prohibited data destination location, permit the tracking tool to execute.
Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for identifying data processing activities associated with various data assets based on data discovery results. In accordance various aspects, a method is provided comprising: identifying and scanning data assets to detect a subset of the data assets, wherein each asset of the subset is associated with a particular data element used for target data; generating a prediction for each pair of data assets of the subset on the target data flowing between the pair; identifying a data flow for the target data based on the prediction generated for each pair; and identifying a data processing activity associated with handling the target data based on a correlation identified for the particular data element, the subset, and/or the data flow with a known data element, subset, and/or data flow for the data processing activity.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that utilize a repository of metadata-based recommendations to classify data sources using metadata from the data sources. For example, the disclosed systems can generate a repository of metadata-based recommendations that indicate recommended classifications for objects within data sources through metadata associated with a data source schema. In some instances, the disclosed systems identify metadata from a data source schema associated with the data source. Subsequently, the disclosed systems can match the identified metadata to a metadata-based recommendation via metadata mappings in the metadata-based recommendation repository to select a metadata-based recommendation. Furthermore, the disclosed systems can also utilize a classifier model to generate predicted labels for the data source and update the metadata-based recommendation repository with a mapping between the predicted labels and metadata corresponding to the data source schema of the data source.
This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that utilize a repository of metadata-based recommendations to classify data sources using metadata from the data sources. For example, the disclosed systems can generate a repository of metadata-based recommendations that indicate recommended classifications for objects within data sources through metadata associated with a data source schema. In some instances, the disclosed systems identify metadata from a data source schema associated with the data source. Subsequently, the disclosed systems can match the identified metadata to a metadata-based recommendation via metadata mappings in the metadata-based recommendation repository to select a metadata-based recommendation. Furthermore, the disclosed systems can also utilize a classifier model to generate predicted labels for the data source and update the metadata-based recommendation repository with a mapping between the predicted labels and metadata corresponding to the data source schema of the data source.
Methods, systems, and non-transitory computer readable storage media are disclosed for processing data for a subset of domains in parallel with publishing data to a tenant database for another subset of domains within a shared infrastructure. Specifically, the disclosed system assigns one or more partitions of an intermediate shared processing queue to a set of domains indicated by a scan request from a client device. The disclosed system extracts data from a subset of domains of the set of domains via the one or more partitions and publishes scan results of the subset of domains to the tenant database. Furthermore, the disclosed system extracts, in parallel with publishing the data of the subset of domains, additional data of an additional subset of domains via the one or more partitions of the intermediate shared processing queue.
This disclosure describes some aspects of systems, non-transitory computer-readable media, and computer-implemented methods that generate insightful user interfaces that display data processing activity components from the application codes, data categories for the detected components, and/or modifications of data categories and/or data processing activity components. For example, the disclosed system can utilize the application code scan to categorize one or more data types and/or data processing purposes represented by the various detected data processing activity components. Additionally, the disclosed systems can generate dynamic graphical user interfaces with the data processing activity components and data categories to enable quick and insightful access to a wide breadth of information from an application code scan. Moreover, the disclosed systems can also determine (and display) changes of data processing activity components and/or data categories detected between scans of different versions of the application code.
G06F 8/71 - Gestion de versions Gestion de configuration
G06F 8/75 - Analyse structurelle pour la compréhension des programmes
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
In various embodiments, a data processing consent capture system may be configured to prompt the data subject to consent to one or more types of data processing (e.g., to provide a desired consent) in response to identifying particular cookies (e.g., or types of data processing) that a data subject has not consented to. The system may, for example, substantially automatically prompt the data subject to consent for one or more particular types of data processing in response to determining that the user (e.g., data subject) has requested that a website or other system perform one or more functions that are not possible without a particular type of consent from the data subject. The system may, for example, prompt the user to consent in time for a certain interaction with the website, application, etc.
In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for mapping the existence of target data within computing systems in a manner that does not expose the target data to potential data-related incidents. In accordance with various aspects, a method is provided that comprises: receiving a source dataset that comprises a label assigned to a data element used by a data source in handling target data that identifies a type of target data and data samples gathered for the data element; determining, based on the label, that the data samples are to be anonymized; generating supplemental anonymizing data samples associated with the label that comprise fictitious occurrences of the type of the target data; generating a review dataset comprising the supplemental anonymizing data samples intermingled with the data samples; and sending the review dataset to a review computing system.
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Digital media in the form of downloadable webcasts, podcasts, audio and video files, for use on mobile devices in the fields of responsible artificial intelligence (AI), AI governance, privacy management, consent management, compliance, ethics, environmental sustainability and responsibility, carbon accounting, reduction and offsetting, environmental, social, and corporate governance (ESG), and ESG program management. Entertainment services, namely, providing podcasts and webcasts in the fields of responsible artificial intelligence (AI), privacy management, consent management, compliance, AI governance, ethics, environmental sustainability and responsibility, carbon accounting, reduction and offsetting, environmental, social, and corporate governance (ESG) and ESG program management.
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
(1) Digital media in the form of downloadable webcasts, podcasts, audio and video files, for use on mobile devices in the fields of responsible artificial intelligence (AI), AI governance, data privacy management, consumer consent management, compliance with privacy legislation, environmental sustainability and responsibility, carbon accounting, reduction and offsetting, environmental, social, and corporate governance (ESG), and environmental, social, and corporate governance (ESG) program management (1) Entertainment services, namely, providing podcasts and webcasts in the fields of responsible artificial intelligence (AI), data privacy management, consumer consent management, compliance with privacy legislation, AI governance, environmental sustainability and responsibility, carbon accounting, reduction and offsetting, environmental, social, and corporate governance (ESG) and environmental, social, and corporate governance (ESG) program management
76.
Systems and methods for mitigating risks of third-party computing system functionality integration into a first-party computing system
In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for integrating third party computing system functionality into a first party computing system by providing a risk management and mitigation computing system configured to analyze a risk of integrating the functionality provided by the third party computing system and facilitating implementation of one or more data-related controls that include performing computer-specific operations to mitigate and/or eliminate the identified risks. For example, the risk management and mitigation computing system can access risk data in tenant computing systems to determine a risk score related to the integration of the third party computing system functionality based on risks determined during prior integrations of the third party computing system functionality by other tenant computing systems. The risk management and mitigation computing system can generate a recommended control when integrating the third party computing system functionality.
Methods, systems, and non-transitory computer readable storage media are disclosed for updating the priority of classifiers in a classifier model. Specifically, the disclosed systems execute operations to extract data elements from a digital dataset. The disclosed system generates first classifier labels for a first subset of data elements (e.g., a test dataset) by utilizing a classification model to apply a predetermined order of classifiers to the first subset of data elements. The disclosed systems utilize the first classifier labels to determine a priority order for the classifiers for applying to a second subset of data elements the digital dataset. Using the determined priority order of the classifiers, the disclosed systems can generate second classifier labels for a second subset of data elements by utilizing the classifier model to apply the classifiers according to the priority order.
Methods, systems, and non-transitory computer readable storage media are disclosed for updating the priority of classifiers in a classifier model. Specifically, the disclosed systems execute operations to extract data elements from a digital dataset. The disclosed system generates first classifier labels for a first subset of data elements (e.g., a test dataset) by utilizing a classification model to apply a predetermined order of classifiers to the first subset of data elements. The disclosed systems utilize the first classifier labels to determine a priority order for the classifiers for applying to a second subset of data elements the digital dataset. Using the determined priority order of the classifiers, the disclosed systems can generate second classifier labels for a second subset of data elements by utilizing the classifier model to apply the classifiers according to the priority order.
Various embodiments provide methods, apparatus, systems, computing devices, computing entities, and/or the like for identifying targeted data for a data subject across a plurality of data objects in a data source. In accordance with one embodiment, a method is provided comprising: receiving a request to identify targeted data for a data subject; identifying a first data object using metadata for a data source that identifies the first data object as associated with a first targeted data type for a data portion from the request; identifying a first data field from a graph data structure of the first data object that identifies the first data field as used for storing data having the first targeted data type; and querying the first data object based on the first data field and the data for the first targeted data type to identify a first targeted data portion for the data subject.
Techniques are disclosed for usage-tracking of various information security (InfoSec) entities for tenants/organization onboarded on an instant multi-tenant security assurance platform. The InfoSec entities include policies, procedures, controls and evidence tasks. A policy or procedure is enforced by implementing one or more controls, and the collection of one or more evidence tasks proves/verifies the implementation of a control. The InfoSec entities are linked to each other across the platform and accrue a number of benefits for the tenants. These include generating a security questionnaire response (SQR), defining a readiness project and an audit project, sharing InfoSec entities encompassing the various products of a tenant, automating risk assessment, automatic collection of evidence tasks for verifying the implementation and/or operational state/status of various mitigating controls, etc.
Aspects of the present invention provide methods, systems, and/or the like for (1) receiving a set of delegates; (2) generating a corresponding GUI for each delegate in the set of delegates, wherein the corresponding GUI is configured with a respective display element that provides a request for the corresponding data unit and an input element for receiving the corresponding data unit; (3) generating at least one corresponding delegate record for each delegate of the set of delegates, wherein the at least one corresponding delegate record identifies the corresponding data unit and the corresponding graphical user interface and is stored in a centralized repository; (4) generating a corresponding electronic communication for each delegate of the set of delegates, wherein the corresponding electronic communication comprises a link to access the corresponding GUI; and (5) sending the corresponding electronic communication for each delegate of the set of delegates to the corresponding assignee.
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie
G06F 9/44 - Dispositions pour exécuter des programmes spécifiques
82.
MANAGING THE DEVELOPMENT AND USAGE OF MACHINE-LEARNING MODELS AND DATASETS VIA COMMON DATA OBJECTS
Methods, systems, and non-transitory computer readable storage media are disclosed for managing implementation of machine-learning models within computing environments according to system requirements frameworks via common data objects. The disclosed system generates a common data object to represent an implementation of a machine-learning model with a data process. For example, the disclosed system determines attribute values of the common data object according to data objects representing the machine-learning model and related datasets. Furthermore, the disclosed system utilizes the common data object to validate the machine-learning model according to a digital representation of a system requirements framework that includes usage requirements for machine-learning models to store, process, transmit, or otherwise handle specific data types in specific ways for the one or more data processes within a computing environment. The disclosed systems also perform operations to implement, suspend, or otherwise modify the machine-learning model or datasets based on the validation.
Methods, systems, and non-transitory computer readable storage media are disclosed for determining clusters of similar digital documents using unique document signatures. Specifically, the disclosed system processes digital text in a digital document to tokenize character strings (e.g., words) in the digital document by combining a subset of character values and string lengths in the character strings. Additionally, the disclosed system generates a document signature for the digital document by combining subsets of tokens generated for the digital document into a token sequence indicative of the digital text in the digital document. The disclosed system determines a cluster of similar digital documents including the digital document by comparing the document signature of the digital document to document signatures corresponding to a plurality of digital documents.
Methods, systems, and non-transitory computer readable storage media are disclosed for routing digital content items to priority-based processing queues based on classifications of the digital content items according to one or more system requirements frameworks. Specifically, the disclosed system scans and classifies digital content items at a digital data repository based on data types included in the digital content items. The disclosed system utilizes a classification model with a classification profile to classify the digital content items according to one or more system requirements frameworks and routes the digital content items to priority-based processing queues according to priority levels indicated by the classifications. Furthermore, the disclosed system provides indications of classifications of the portions of the digital content items (e.g., to indicate high priority data). The disclosed system can also perform additional computing operations on the digital content items according to the routing via the priority-based processing queues.
Methods, systems, and non-transitory computer readable storage media are disclosed for managing implementation of machine-learning models within computing environments according to system requirements frameworks via common data objects. The disclosed system generates a common data object to represent an implementation of a machine-learning model with a data process. For example, the disclosed system determines attribute values of the common data object according to data objects representing the machine-learning model and related datasets. Furthermore, the disclosed system utilizes the common data object to validate the machine-learning model according to a digital representation of a system requirements framework that includes usage requirements for machine-learning models to store, process, transmit, or otherwise handle specific data types in specific ways for the one or more data processes within a computing environment. The disclosed systems also perform operations to implement, suspend, or otherwise modify the machine-learning model or datasets based on the validation.
G06N 3/10 - Interfaces, langages de programmation ou boîtes à outils de développement logiciel, p. ex. pour la simulation de réseaux neuronaux
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
G06N 3/0442 - Réseaux récurrents, p. ex. réseaux de Hopfield caractérisés par la présence de mémoire ou de portes, p. ex. mémoire longue à court terme [LSTM] ou unités récurrentes à porte [GRU]
Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing dynamic request queues to process electronic requests in a shared infrastructure environment. The disclosed system dynamically generates a plurality of separate request queues for tenant computing systems that utilize a shared processing infrastructure to issue electronic requests for processing by various recipient processors (e.g., one or more processing threads) by separating a primary request queue into the separate requests queues based on the tenant computing systems. The disclosed system also generates a plurality of queue order scores for the request queues based in part on a processing recency of each of the request queues and whether the request queues have pending electronic requests. The disclosed system processes electronic requests in the request queues by selecting a request queue based on the queue order scores and processing a batch of electronic requests utilizing a recipient processor.
H04L 47/62 - Ordonnancement des files d’attente caractérisé par des critères d’ordonnancement
H04L 67/1031 - Commande du fonctionnement des serveurs par un répartiteur de charge, p. ex. en ajoutant ou en supprimant de serveurs qui servent des requêtes
H04L 47/52 - Ordonnancement selon la bande passante des files d'attente
H04L 47/60 - Ordonnancement des files d’attente en implémentant un ordonnancement hiérarchique
87.
Data processing systems and methods for automatically detecting target data transfers and target data processing
Aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for protection of system software, or data from destruction, unauthorized modification, and/or unauthorized disclosure securing by, for example, detecting the transfer and/or processing of target data. Accordingly, a method is provided that involves: scanning a software application to identify functionality configured for processing target data; identifying fields associated with the functionality; identifying metadata associated with a field; generating, from the metadata, an identification of a type of data associated with the field; determining a location based on the processing of the target data by the functionality; determining a risk associated with the functionality processing the target data based on the location and the type of data; determining that the risk satisfies a threshold level of risk; and in response, causing an action to be performed to mitigate the risk.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Digital media in the form of downloadable webcasts, podcasts,
multimedia files containing audio for use on mobile devices in the
fields of privacy management, consent management, compliance,
ethics, environmental, social, and corporate governance (ESG), and
ESG program management Entertainment services, namely, providing podcasts and webcasts
in the fields of privacy management, consent management,
compliance, ethics, environmental, social, and corporate governance
(ESG) and ESG program management
09 - Appareils et instruments scientifiques et électriques
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Digital media in the form of downloadable podcasts, multimedia files
containing audio and video for use on mobile devices in the fields of
responsible artificial intelligence (AI), AI governance, privacy
management, consent management, compliance, ethics,
environmental, social, and corporate governance (ESG), and ESG
program management Entertainment services, namely, providing podcasts and webcasts in
the fields of responsible artificial intelligence (AI), AI governance,
environmental sustainability and responsibility, carbon accounting,
reduction and offsetting
90.
Data processing systems and methods for synching privacy-related user consent across multiple computing devices
A privacy-related consent extension and data processing system may be configured to automatically extend one or more privacy-related consents for a user of a first computing device to a second computing device. In various embodiments, the system is configured to provide a computer-readable indicium (indicia) on a previously unknown computing device upon initiation of a transaction between a user and an entity collecting and processing privacy data. In response to a user using a known computing device to scan the computer-readable indicium, in various embodiments, the system may provide the ability to share user consent data provided by the first known device to the second unknown device, allowing the user to provide consent without manually re-entering privacy and consent preferences.
In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for managing implementation of data controls for computing systems. In various aspects, a method is provided that comprises: comparing a first version of a dataset describing a regulatory framework to a second version of the dataset to identify a change to a data control; in response: processing, using a featurization technique, a portion of the dataset to generate a feature representation of the change that comprises feature attributes representing the change; processing, using a first machine-learning model, the feature representation to generate tags representing characteristics of the change; processing, using a second machine-learning model, the tags to generate an applicable domain; identifying, based on the domain, a computing system affected by the change; and in response, coordinating an action to be performed for the computing system to address the change.
Methods, systems, and non-transitory computer readable storage media are disclosed for generating action recommendations modifying physical emissions sources of an entity based on past and modeled emissions for the entity. Specifically, the disclosed system monitors emissions produced by an entity by determining a number of emissions sources corresponding to an entity and a plurality of emissions values for the emissions sources. Additionally, the disclosed system determines a plurality of constraints corresponding to the entity. The disclosed system also determines goals for the entity including target emissions values. The disclosed system utilizes a modified gradient descent model to iteratively adjust emissions values for the physical emissions sources to obtain the target emissions values according to the constraints. The disclosed system generates action recommendations for modifying the physical emissions sources utilizing the modified gradient descent model and provides the action recommendations for display within a graphical user interface.
G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
Methods, systems, and non-transitory computer readable storage media are disclosed for generating action recommendations for generating action recommendations for modifying physical emissions sources of an entity based on forecasting and monitoring emissions production for the entity utilizing machine-learning models. Specifically, the disclosed system forecasts emissions produced by an entity by utilizing a plurality of different forecasting machine-learning models corresponding to different physical emissions sources to generate forecasted source attributes. Additionally, the disclosed system combines the forecasted source attributes to generate a plurality of forecasted emissions value modifications for a future time period. The disclosed system generates action recommendations for modifying the physical emissions sources based on the forecasted emissions value modifications. In additional embodiments, the disclosed system tracks emissions of the entity during the future time period and generate additional action recommendations in response to detecting deviations from forecasted emissions production.
G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
System and methods are disclosed for redacting analyzing unstructured data in a request for data associated with a data subject to determine whether the unstructured data is relevant to the request. The relevancy of pieces of the unstructured data may be determined by determining a categorization for each such piece of unstructured data and comparing them to known personal data associated with the data subject having the same categorization. Pieces of the unstructured data that do not match known personal data having the same categorization are redacted from the request before the request is processed.
In general, various aspects provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for performing data discovery on a target computing system. In various aspects, a third party computing connects, via a public data network, to an edge node of the target computing system and instructs the target computing system to execute jobs to discover target data stored in data repositories in a private data network in the target computing system. In some aspects, the third party computing system may schedule the jobs on the target computing system based on computing resource availability on the target computing system.
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
G06Q 10/063 - Recherche, analyse ou gestion opérationnelles
A method, in various aspects, comprises: (1) receiving a query from a first party computing system related to integrating third party computing functionality into the first party computing system; (2) identifying a set of third party entities that provide the third party computing functionality; (3) accessing integration data; (4) identifying a set of reference entities, the set of reference entities including, for each respective third party entity, a respective reference entity that has previously integrated the third party computing into a respective reference entity computing system associated with the respective reference entity; (5) determining second integration data with respect to the set of reference entities integrating the third party computing functionality; (6) generating, based on the first integration data and the second integration data, data responsive to the query that is specific to the first party computing system; and (7) taking an action with respect to the data.
G06Q 10/0635 - Analyse des risques liés aux activités d’entreprises ou d’organisations
G06Q 10/067 - Modélisation d’entreprise ou d’organisation
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 15/76 - Architectures de calculateurs universels à programmes enregistrés
97.
Mapping entities in unstructured text documents via entity correction and entity resolution
Methods, systems, and non-transitory computer readable storage media are disclosed for correcting entity detection errors with entity correction and resolution in optical character recognition for digitization of physical documents. Specifically, the disclosed system utilizes named entity recognition to extract entities from character strings (e.g., words) in a digital text document. The disclosed system also tokenizes the character strings in the digital text document based on attributes of the character strings. Furthermore, the disclosed system compares the extracted entities and tokenized character strings to determine similarity metrics between the extracted entities and tokenized character strings. The disclosed system also compares extracted entities to character strings including special/numerical characters to determine similarity metrics indicating correlation probabilities between entities and character strings. The disclosed systems generate mappings between the tokens and entities based on the similarity metrics to resolve entities to likely corresponding character strings while correcting for errors during entity extraction.
Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for implementing and managing access to particular data based on access controls for implementing purpose restrictions and/or consent restrictions. In various aspects, a method is provided that comprises: receiving a request transmitted by an application executing on a client computing system and requesting access to a dataset, wherein each data record of the dataset comprises data elements; identifying, based on the application, a purpose for the application requesting access to the dataset; referencing, based on the purpose, an applicable purpose-based access-control policy to identify an authorization token; and providing the authorization token, wherein the storage computing system provides the client computing system with a view of the dataset based on the token with the view having a data element returning modified data in a manner compliant with the applicable purpose-based access-control policy.
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating multidimensional risk visualizations depicting severity and frequency and for predicting risk mitigation strategies. For example, the disclosed systems generate multidimensional risk visualizations that present visual representations of risk severity and risk frequency in multidimensional formats, including many risk dimensions at once. In certain cases, the disclosed systems further utilize a particular machine learning model such as a strategy prediction neural network to generate predicted mitigation strategies based on risk data.
Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing machine-learning models to deduplicate electronic survey questions of electronic surveys or questionnaires in real-time. Specifically, the disclosed system maps electronic survey questions to specific domain classifications by utilizing a machine-learning model to classify portions of electronic surveys based on context within the portions of the electronic surveys. Additionally, the disclosed system utilizes the mappings of electronic survey questions to domain classifications to determine whether to deduplicate specific questions that are semantically similar and within the same domain classifications. For instance, the disclosed system utilizes natural language processing to find semantically similar questions across a plurality of electronic surveys and deduplicate the similar questions if their domain classifications are the same.
