Systems, computer program products, and methods are described herein for predictive generation of electronic query data. The present invention is configured to electronically receive a query string associated with an administrative body, wherein the query string corresponds to a response field, and wherein the response field is configured to receive a response string; retrieve, from a database associated with an entity, information associated with the administrative body; determine an administrative record associated with the administrative body, wherein the administrative record comprises one or more prior response strings; generate one or more customized autofill options for the response string based on at least the information associated with the administrative body and the administrative record associated with the administrative body; and transmit control signals configured to cause the endpoint device of the user to display, on a graphical user interface, the one or more customized autofill options to the user.
G06F 40/274 - Conversion de symboles en motsAnticipation des mots à partir des lettres déjà entrées
G06F 16/3329 - Formulation de requêtes en langage naturel
2.
System and Method for Generative Design Based Real-Time Restricted Sub Application Setup with Non-Production Data Architectural Flow Determination with Enterprise Scoped Large Language Injection Model
Systems and processes enhance cybersecurity by dynamically generating a decoy sub-application that operates parallel to the primary application using generative design and a large language model. The core feature involves real-time anomaly detection within application traffic, utilizing AI to assess threats and orchestrate appropriate responses. Upon identifying potential security threats, the system employs generative design principles to architect a restricted-functionality sub-application, deploying it instantly to engage and analyze the attack vectors without compromising sensitive production data. The sub-application is isolated through software-defined networking, ensuring that its operations do not affect the primary application's functionality. Additionally, sophisticated traffic redirection mechanisms are employed to divert suspicious traffic from the primary to the decoy application, thereby protecting the integrity while allowing detailed threat analysis. This dual-capability system not only safeguards against disruptions but also enhances adaptive security measures through continuous learning and system adjustments.
Apparatus, methods and systems for contextual prediction processing is provided. Methods may include receiving a conversation from an entity. The conversation may include current utterance, previous utterances and details. Methods may include using an action-topic ontology to build, using data retrieved from the current utterance, a conversation frame that corresponds to the current utterance. Methods may include merging the conversation frame with data, retrieved from the previous utterances and the details, to generate a target conversation frame. Methods may include validating the target conversation frame to prevent looping over historic data in the event that the current utterance fails to add relevant information. Methods may include generating an enhanced contextual utterance based on algorithms and the target conversation frame. The enhanced contextual utterance may be used to understand the current utterance in a context of the conversation. Methods may include returning the enhanced contextual utterance to the entity.
Intelligently determination of intent of a resource provider when attempting to delete a resource event device, specifically, the resource event credentials associated with the resource event device, from a network location. Intent is determined by implementing Artificial Intelligence (AI) to analyze the resource provider's historical data to determine a probable/possible intent and, in response, queries are presented to the resource provider that attempt to confirm the probable/possible intent as the actual intent. In response to determining the intent, the invention is configured to perform one or more actions that are based on the determined intent.
A system includes a memory configured to store user profiles associated with a plurality of users and an interactive voice response (IVR) system configured to service calls. The system includes processors configured to receive a call from a first user, generate a first voice interaction configured to prompt the first user to perform an utterance of a second voice interaction, and detect the utterance of the second voice interaction. The processors are configured to execute a first machine-learning model trained to identify speech and voice characteristics of the first user and to generate a third voice interaction based on the identified speech and voice characteristics. In response to identifying an intent and one or more named entities of the request, the processors are configured to initiate the execution of one or more interactions with the first user profile in accordance with the identified intent and one or more named entities.
Arrangements for providing unauthorized activity detection are provided. A computing platform may receive a request for transaction from a transaction processing card via a card reader of a transaction processing device. The computing platform may dynamically generate a validation code. The computing platform may transmit the validation code to the transaction processing card. In some examples, the computing platform may receive, from the transaction processing card, an encrypted version of the validation code. The code may be encrypted by the transaction processing card using a key associated with the transaction processing card. The computing platform may attempt to decrypt the encrypted code with a key associated with the transaction processing device. If the decryption is successful, the transaction may continue. If decryption is not successful, the transaction may be denied and a notification indicating that the transaction processing card is compromised may be generated and transmitted to a computing device.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
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
7.
SYSTEM AND METHOD FOR CONTROLLING AND SECURING NETWORK CONNECTIVITY USING SWARM INTELLIGENCE
Embodiments of the present invention provide a system for controlling and securing network connectivity using swarm intelligence. The system is configured for determining initiation of a network connection from a user device of a user with a network device, performing encryption of data packets associated with the initiation of the network connection before transmitting the data packets to the network device, transmitting the encrypted data packets associated with the initiation of the network connection to the network device, extracting one or more identifiers associated with the network device, determining if the network device is secure, via an artificial swarm intelligence engine, and performing an action comprising establishing the network connection based on determining that the network device is secure to connect or denying the network connection based on determining that the network device is not secure to connect.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
8.
Automated Teller Machine (ATM) Exception Identification and Analysis
Arrangements for identifying, analyzing, and remediating automated teller machine (ATM) exceptions are provided. A computing platform may configure an exception mapping table to match an exception code to a corresponding exception type. The computing platform may receive exception codes associated with one or more automated teller machines (ATMs). The computing platform may map the exception codes to corresponding exception types. The computing platform may compile exception ranking information into a ranked list. The computing platform may identify a subset of ATMs to take action on. The computing platform may identify actions to remediate issues related to the exception codes. The computing platform may automatically execute the identified actions.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
A system includes a memory configured to store user profiles associated with a plurality of users and an interactive voice response (IVR) system configured to service calls. The system includes processors configured to receive a call from a first user, generate a first voice interaction configured to prompt the first user to perform an utterance of a second voice interaction, and detect the utterance of the second voice interaction. The processors are configured to detect the utterance of the second voice interaction, execute a machine-learning model trained to identify speech and voice characteristics of the first user and to generate a third voice interaction based on the identified speech and voice characteristics, dynamically adjust IVR response features associated with the third voice interaction based on the identified speech and voice characteristics, and output the third voice interaction in accordance with the dynamically adjusted one or more IVR response features.
Arrangements for providing unauthorized activity detection are provided. A computing platform may receive an indication that a transaction has been initiated at a transaction processing device. The computing platform may receive, from one or more sensors arranged on the transaction processing card, capacitance data associated with a capacitance detected when the transaction processing card is inserted into the card reader. The computing platform may execute a machine learning model using, as inputs, the capacitance data, to output any detected discrepancies between the current capacitance data and expected capacitance data. If a discrepancy is detected, the computing platform may identify that a skimming device is present at the card reader of the transaction processing device. A notification indicating that the skimming device is present may be generated and transmitted to, for instance, the transaction processing card and may cause a light emitting diode on the transaction processing card to illuminate.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
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
Apparatus and methods for proactively and preemptively communicating with a user interacting with a software application are provided. The apparatus and methods may include an artificial intelligence/machine learning communication engine monitoring and tracking a user's interactions. The apparatus and methods may include the communication engine determining if the user requires further training, if the interaction is fraudulent, and pre-empting requests for information the user may commence. The apparatus and methods may include the communication engine creating and displaying training materials for the user to complete, revoking access if fraud is present, and proactively providing information before the user requests the information.
The present invention relates to systems and methods for proactive real-time anomaly detection in cross-environment RPC (Remote Procedure Call) communications within computing systems. Utilizing an Intelligent GraphRPC Method, this invention integrates advanced graph analysis techniques to enhance fault detection and workflow management. The method features a dual-graph approach, employing both real-time and aggregated dependency graphs, which allows for continuous monitoring and analysis of RPC interactions to detect and prevent unauthorized or misconfigured RPC calls between staging and production environments. An ingestion pipeline further supports the system by aggregating and archiving call graph data, providing beneficial insights into service dependencies and potential security risks. This proactive anomaly detection system is designed to seamlessly integrate into existing monitoring and alerting frameworks, providing a robust solution to safeguard data integrity and operational stability, thereby minimizing losses and reputational damage due to data breaches and system disruptions.
Systems, apparatus and methods for creating and enforcing real-time counter-malicious rules are provided. Methods may include monitoring, using a quantum processing unit, interactions on a network. Methods may include identifying, using the quantum processing unit, one or more fraudulent activities included in the interactions. Methods may include amalgamating, using the quantum processing unit, the fraudulent activities. Methods may include rebuilding, using the quantum processing unit, one or more fraudster rules used by one or more entities executing the one or more fraudulent activities. Methods may include building, using the quantum processing unit, one or more elastic counteractive rules, said elastic counteractive rules counteracting the one or more fraudster rules. Methods may include executing, using the quantum processing unit, the elastic counteractive rules within the network. Methods may also include halting, using the quantum processing unit, the one or more fraudulent activities within the network using the elastic counteractive rules.
G06N 10/40 - Réalisations ou architectures physiques de processeurs ou de composants quantiques pour la manipulation de qubits, p. ex. couplage ou commande de qubit
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
15.
GRAPHICS PROCESSING UNIT (GPU) OPTIMIZATION USING HASH TABLES
A computing platform may receive a GPU processing request for processing by a GPU system. The computing platform may identify an operation requested by the GPU processing request. The computing platform may identify whether or not the operation is stored in a hash table. Based on identifying that the operation is not stored in the hash table, the computing platform may identify whether an approximate match of the operation is stored in the hash table. Based on identifying that the approximate match is stored in the hash table, the computing platform may identify a first key stored, in the hash table, along with the approximate match. The computing platform may identify, using the first key, a location of a solution to the approximate match of the operation. The computing platform may obtain, from the location, the solution to the approximate match of the operation, and may apply the solution.
A system is provided for real-time monitoring and remediation of network intrusion using an intelligent application programming interface. In particular, the system may monitor and track, in real time, the various computing devices within a distributed networked system. The system may use one or more trained artificial intelligence models to analyze incoming network requests and detect anomalies within the body of network requests, and based on the analysis, implementing one or more countermeasures (e.g., request throttling, rate limiting, allocation of additional computing resources, and/or the like) in response. In some embodiments, the one or more AI models may be configured to generate intrusion mitigation and/or remediation plans in response to any detected anomalies. The output of the AI models may then be wrapped with additional data that may enhance the anomaly detection process.
A computer implemented system and method are disclosed involving technological advancements in the processing of electronic transaction processing results. The system may comprise a computer apparatus implementing a checking account system, a savings account system, a merchant account and investment account on a funds management system, and one or more computer systems and mobile devices including a communication interface, processor, memory storing computer-executable instructions, and savings modules. Reward amounts may be calculated based on various techniques.
G06Q 40/06 - Gestion de biensPlanification ou analyse financières
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
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
Arrangements for providing unauthorized activity detection are provided. A computing platform may receive an indication that a transaction has been initiated at a transaction processing device. The platform may receive, from one or more sensors arranged on the transaction processing card, magnetic field data associated with a magnetic field detected when the transaction processing card is inserted into the card reader. The platform may execute a machine learning model using, as inputs, the magnetic field data, to output any detected discrepancies between the current magnetic field data and expected magnetic field data. If a discrepancy is detected, the computing platform may identify that a shimming device is present at the card reader of the transaction processing device. A notification indicating that the shimming device is present may be generated and transmitted to, for instance, the transaction processing card.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
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
19.
Automated teller machine (ATM) anomaly detection and resolution
Arrangements for detecting and resolving automated teller machine (ATM) anomalies are provided. A computing platform may receive information related to one or more automated teller machines (ATMs) that may include one or more anomalies. The computing platform may preprocess the information to remove one or more false positives from the information. The computing platform may apply anomaly detection logic to the preprocessed information to identify one or more anomalies. The computing platform may output one or more anomaly codes that correspond to the identified one or more anomalies. The computing platform may identify and subsequently execute one or more actions to resolve the one or more anomalies.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
20.
NATURAL LANGUAGE GENERATION SYSTEM FOR AUTOMATED TRANSLATION OF DIGITAL MULTIMEDIA
Systems, computer program products, and methods are described herein for automated translation of digital multimedia. The present disclosure is configured to receive, from a user input device, a search request; determine the response for the search query in a first natural language, wherein the response comprises digital multimedia; reconfigure the response for display on the user input device in the preferred natural language, wherein reconfiguring further comprises: determining an intermediate natural language based on a lexical similarity with the preferred natural language; translating, using a first natural language translation subsystem, the response from the first natural language to the intermediate language; and translating, using a second natural language translation subsystem, the response from the intermediate language to the preferred natural language; and display the reconfigured response on the user input device in the preferred natural language.
G06F 40/40 - Traitement ou traduction du langage naturel
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
H04N 21/43 - Traitement de contenu ou données additionnelles, p. ex. démultiplexage de données additionnelles d'un flux vidéo numériqueOpérations élémentaires de client, p. ex. surveillance du réseau domestique ou synchronisation de l'horloge du décodeurIntergiciel de client
H04N 21/439 - Traitement de flux audio élémentaires
21.
COLLABORATIVE VERIFIED USER PLATFORM USING DISTRIBUTED LEDGER TECHNOLOGY
Aspects of the disclosure relate to a collaborative verified user platform using distributed ledger technology. A collaborative verified user platform may identify changes to user information stored at a distributed ledger. The platform may retrieve changes from a remote database. The platform may update the distributed ledger based on the changes. The platform may receive, from a second user device, a request to access the user information. The platform may establish a secure channel. The platform may process one or more secure requests associated with a venture corresponding to both the first user device and the second user device. The platform may detect a permission violation. The platform may initiate security actions based on the permission violation. The platform may receive an updated cyber contract corresponding to the user information. The platform may update permissions based on the updated cyber contract.
Apparatus and methods for quantum-computing based file remediation are provided. A quantum file remediation program on a computer system with a standard processor and an “N”-qubit processor may receive a network file. When a file attribute score determined on the standard processor deviates by more than a predetermined amount from a baseline score, the program may initialize a quantum circuit. A deep learning framework using a quantum generative adversarial network (QGAN) may run on the quantum circuit and generate a remediated file. When the QGAN session ends, the quantum circuit may be collapsed and the original network file may be replaced by the remediated file.
Systems, computer program products, and methods are described herein for migrating application functionality using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive, via a learning agent, a transaction incident associated with a source application in a transaction, wherein the transaction comprises one or more applications, and wherein the learning agent comprises learning the applications' functionality; determine, using a real time incident listener, a scope of the transaction incident; access an application inventory to determine a target application, wherein the application inventory comprises a database of applications, and wherein the database of applications is associated with an entity that is associated with the system; generate, using a script generator, a script, wherein the script comprises a source function associated with the source application; deploy the script to the target application; and monitor the target application with a federated learning module.
Systems, computer program products, and methods are described herein for automatically generating and implementing password rotations using artificial intelligence. The present invention is configured to identify at least one password rule associated with at least one application; train a machine learning model by applying the at least one password rule; determine, by the trained machine learning model, whether a password rotation requirement is present for the at least one application; generate, by an artificial intelligence (AI) bot, an updated password for the at least one application in an instance where the password rotation requirement is present; validate the updated password for the at least one application; and automatically update, based on the validation of the updated password, the at least one application with the updated password.
A method is provided that includes receiving a request to perform an interaction that includes user data and device data. The method includes splitting the user data into one or more logical data components. The method includes comparing the one or more logical data components to one or more predetermined validation thresholds. The method includes determining whether the one or more logical data components satisfy the one or more predetermined validation thresholds. In response to determining that the one or more logical data components satisfy the one or more predetermined validation thresholds, the method includes obfuscating the one or more logical data components to generate one or more unique identifiers, and obfuscating the device data to generate a unique device identifier. The method includes generating an authentication response configured to authorize the external entity server to perform the interaction that includes the unique identifiers and unique device identifier.
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 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
Systems, computer program products, and methods are described herein for network event data streaming and processing via modular network event data architecture. The present disclosure includes receiving a plurality of network event data in real-time, determining a feature of at least one network event data, labeling the at least one network event data with a label corresponding with the feature, retrieving a preconfigured routing path, routing, from the input module to a first processing module, the at least one network event data, wherein the first processing module is reusable for other preconfigured routing paths, and transforming the network event data in accordance with the predetermined rule.
Systems, computer program products, and methods are described herein for authenticating digital IDs over an electronic network using dual authentication in a distributed network. The present disclosure is configured to identify a primary communication channel from a user device; generate an authentication prompt for the primary communication channel; transmit the authentication prompt to the user device; identify, based on the authentication prompt, an authentication credential from a secondary communication channel associated with the user device; and authenticate the authentication credential based on a digital identifier associated with the user device.
In response to detecting that a first error associated with processing a first job by a first software application has occurred, a jobs manager obtains a first error message associated with the first error and determines whether the first error message is one of a plurality of known error messages associated with the first software application. In response to determining that the first error message is one of the known error messages associated with the first software application, the jobs manager obtains a first known recovery plan associated with the first error message and performs one or more recovery steps associated with the first known recovery plan to resolve the first error associated with the first software application.
In response to determining that a first error message associated with a first software application is not a known error message associated with the first software application, a jobs manager determines a second software application of a plurality of software applications that is associated with a same or similar known error message as the first error message and obtains a first known recovery plan associated with the same or similar known error message. The jobs manager then generates a customized recovery plan for the first software application based at least in part upon the first known recovery plan, wherein the customized recovery plan comprises one or more customized recovery steps associated with resolving the first error. The jobs manager performs one or more of the customized recovery steps associated with the customized recovery plan to resolve the first error associated with the first software application.
After generating a first customized recovery plan to resolve a first error associated with a first error message generated by a first software application, a jobs manager obtains identities of an input system, an output system or a combination thereof associated with the first software application. In response to determining that a second software application is associated with the same or similar input system, the same or similar output system, or the combination thereof as the first software application, the jobs manager determines that the first error associated with the first software application is predicted to occur relating to the second software application. Thereafter, the jobs manager generates a second customized recovery plan for the second software application based at least in part upon the first customized recovery plan generated for the first software application.
Systems, computer program products, and methods are described herein for verifying devices using advanced computational models for data analysis and automated processing. The present disclosure is configured to initiate a resource transaction, wherein the resource transaction is initiated via a sender device, and wherein the resource transaction comprises transferring a resource from a sender resource container to a receiver resource container via the sender device and a receiver device; generate a primary contract, wherein the primary contract comprises encrypting a data packet associated with the resource transaction and wherein the data packet comprises resource transaction details; generate a secondary contract, wherein the secondary contract comprises verifying the receiver device; and execute the resource transaction, wherein executing the resource transaction comprises providing the data packet to a sender entity, and wherein the sender entity is associated with the sender resource container.
A method is provided that includes receiving an interaction request that comprises interaction data. The method includes processing the interaction data using software applications in an interaction validation pathway, receiving a content error associated with processing the interaction data in the interaction validation pathway, and determining whether a pre-determined content correction is configured to correct the content error. If not, the method includes generating a content correction using a machine learning model, generating a simulated environment for processing the interaction data with a simulated interaction validation pathway, applying the content correction to the first content error in the simulated environment, and determining whether the content correction corrects the content error in the simulated environment. If so, the method includes generating modified interaction data by applying the first content correction to the first content error, and processing the modified interaction data using the interaction validation pathway.
A method for dynamically generating a user interface (“UI”), the UI for use with a source application is provided. The method may include tagging each field within the source application to one or more priority levels. The method may include identifying a user accessing the source application. The method may include identifying a user priority level and a plurality of historic pattern behaviors of the user. The method may include generating the UI based on the user priority level and the plurality of historic pattern behaviors. The method may include dynamically monitoring the user's usage. The method may adjust the UI based on the usage. The generating the UI may include adding each field tagged to the user priority level and adding each field associated with the historic pattern behaviors to the UI. The adjusting may include adding, removing and changing at least one field generated on the UI.
Methods for banking at an automated teller machine (ATM) using a mobile device. The ATM may automatically detect the presence of the mobile device in a vicinity of the ATM and initiate contact with the mobile device, or a mobile device may initiate contact with the ATM. After verifying user permission to access the ATM, the mobile device may be enabled to provide user access to one or more of the banking services available at the ATM using the mobile device and to view banking-related information on the mobile device. A mobile application on the mobile device may be used to access the ATM using the mobile device. While a mobile device is accessing the ATM, a screen on the ATM may become inactive for banking services and the option to select banking services directly at the ATM may be disabled.
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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
Apparatus and methods for an artificial intelligence implemented termination by an auditor artificial intelligence (“aAI”) of a malicious artificial intelligence (“mAI”) are provided. The aAI may detect a mAI on a network and determine which data the mAI can access on the network. The aAI may then degrade all or part of the data in various ways to prevent the mAI from producing valid content based on the data. The aAI may also create code and inject the code into the mAI to degrade the mAI's operations. As the mAI may rely on valid data to produce valid output, degrading the data may degrade the mAI.
Embodiments of the invention are directed to systems, methods, and computer program products for proactive resiliency, redundancy and security remediation across a network based on dynamic analysis of technology applications. The invention involves determining whether an entity communication network comprises at least one first redundant technology application associated with the first technology application such that the at least one first redundant technology application renders at least one processing activity of the first technology application resilient. Here, the invention involves constructing network vulnerability components associated with a first data flow comprising an open vulnerability component, an unauthorized technology component, and an open security component. The invention may determine a prognostic failure associated with the first data flow based on determining that the entity communication network does not comprise at least one first redundant technology application associated with the first technology application.
H04L 41/0654 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant la reprise sur incident de réseau
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/16 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel
A system is provided for implementing time-restricted access control to electronic digital resources. In some embodiments, the custom set of executable code used to generate the digital resource may provide granular control over access restrictions for accessing, viewing, and/or transferring the digital resource. Such access restrictions may include time duration restrictions, access frequency restrictions, data quality restrictions, and/or the like. In this way, the system may limit access to the digital resource in a secure manner.
Systems, computer program products, and methods are described herein for implementing real time protocol modifications for address resolutions protocols in a network environment. The present disclosure is configured to identify an address resolution protocol (ARP) cache table comprising an internet protocol (IP) address and a media access control (MAC) address for a communication mapping(s); determine a firewall property(ies) of the ARP cache table for the communication mapping(s); compare the firewall property(ies) to at least one normal firewall property and determine whether the firewall property(ies) is anomalous compared to the normal firewall property(ies); automatically execute a smart contract, wherein the smart contract comprises an authorization protocol(s) for the ARP cache table and an execution of a homomorphic encryption for the ARP cache table; and protect the ARP cache table based on the execution of the smart contract with the authorization protocol(s) and the homomorphic encryption.
A system for improving performance of a website is disclosed. The system detects web components associated with the website and determines conditional metrics. The conditional metrics indicate a range of conditions under which the performance of the website is evaluated. The system generates a set of test case scripts to emulate various user interactions with the website under various conditions according to one or more conditional metrics. The system executes a first test case script to emulate a first user interaction with a first web element under a first condition. The system determines that a result of the first test case script does not correspond to an expected output. In response, the system performs a corrective action, including updating a code portion associated with the first web element in the source code of the website to a code portion that is configured to provide the expected output.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
40.
Multi-Function Device Having Dynamic Toggle Capabilities
Arrangements for providing multi-functionality device control functions are provided. In some aspects, a request for transaction may be received by a computing platform. The request may include transaction details including selection of a mode of processing, received from a payment device. The computing platform may determine whether the selected mode of payment is crypto currency. If so, the transaction details may be transmitted to a peer-to-peer network for validation of the transaction. If the transaction is validated, a new block, corresponding to the validated transaction, may be generated and added to a blockchain and the transaction may be processed. In some examples, additional details of the transaction may be received and the additional details and the transaction details may be input to a machine learning model. Upon execution of the model, an environmental impact score associated with the transaction and a recommendation may be determined and transmitted to the user.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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
41.
System and method to dynamically analyze representative application data
An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to generate a representative application in a simulation environment based at least in part upon an application data. The processor is further configured to execute the machine learning algorithm to perform one or more obfuscation operations configured to at least partially replace application information of the application data with simulation information of a specific data type; purge the application information from the simulation environment; simulate multiple application operations by the representative application using the simulation information; determine whether the simulated application responses comprise an output that is different from any of those in expected application responses in response to monitoring the simulated application responses during simulation of the application operations; and determine a modification suggestion to multiple application configuration parameters of the application configured to inhibit the output in response to determining the output.
Methods, systems and apparatus for detecting, monitoring and forecasting for compromised electronic communications in an electronic communication system. Methods may include isolating, from a historical database, electronic communications associated with a plurality of senders into individual data capsules. Methods may include generating and storing a predictive analytic profile for each sender based on a communication style identified for each sender. Methods may include filtering out compromised electronic communications using a dynamic quantum filter, the dynamic quantum filter including a dynamic condition set. Filtering may include inserting a quantum signature into each incoming electronic communication. Methods may include retrieving the predictive analytic profile associated with the sender identified for each incoming electronic communication. Methods may include assigning condition values to each electronic communication based on comparing each electronic communication to a corresponding predictive analytic profile. Methods may include determining whether the assigned condition values conform with the dynamic condition set.
Systems and methods for a system architecture for supporting bifurcated data transmission are provided. The system architecture may include a point-of-sale (“POS”) device. The system architecture may include a central server. The POS device may break up a transaction request received from a requestor into micro-data. Each micro-data may include a tiny portion of the transaction request and a header. The header may identify the transaction request and a number that identifies a location of the micro-data within the transaction request. The POS device may send the micro-data to a quantum processor for arranging the micro-data in a queue in a random order. The POS device may also compile a confirmatory data packet including data identifying the point-of-sale device and a total number of the micro-data. The confirmatory data packet and the micro-data, in the random order, may be transmitted to the central server.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
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
44.
Dynamic Feature Optimization Leveraging Quantum Simulation for Fake Account Detection
Robust systems and methods are disclosed for fake account detection on digital platforms, integrating provenance analysis to scrutinize data origins, ownership, and history, thereby unveiling potential sources of fraudulent activities. They leverage dynamic feature generation, using advanced algorithms to assess user behaviors and interactions, ensuring the model stays attuned to the evolving landscape of cyber threats. Incorporating Quantum-assisted optimization, the method employs Quantum algorithms to expedite feature selection, enhancing detection efficiency. Quantum simulation further refines this process, creating sophisticated verification patterns and analytical techniques to distinguish genuine from fake accounts with higher accuracy. A comprehensive analysis amalgamates provenance data, telemetry, and dynamic features, forming a holistic detection approach. This system optimizes features through Quantum simulation, tailoring them to specific business environments, and deploys them via AI-ML DevOps, streamlining orchestration across various operational settings.
G06N 10/60 - Algorithmes quantiques, p. ex. fondés sur l'optimisation quantique ou les transformées quantiques de Fourier ou de Hadamard
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
45.
VIRTUAL REALITY HEADSET AND ARTIFICIAL INTELLIGENCE VIRTUAL ASSISTANT INTEGRATION FOR ADDRESSING A LANGUAGE BARRIER WITH A CUSTOMER
A method for improving service to a user encountering a language barrier. The user may encounter a language barrier when speaking to an agent or using a computer application of an organization. The user may use a VR headset to translate its request for assistance into a language used at the organization and transmit the translated request to an AI virtual assistant. The AI virtual assistant may confirm its understanding of the user's request, determine an agent in a team in the organization that can assist the user, and transfer the user to that agent. The user and the agent may each speak in a language in which they are proficient, even though the other is not proficient in that language, to resolve the user's request. An API may integrate the AI virtual assistant with the VR headset to facilitate real-time communication between the user and the agent.
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
G06Q 40/02 - Opérations bancaires, p. ex. calcul d'intérêts ou tenue de compte
G10L 13/02 - Procédés d'élaboration de parole synthétiqueSynthétiseurs de parole
Webpage integrity is monitored using hash verification. A hash verification process is implemented to detect unauthorized changes to value field(s) in a webpage's source code and, while the user is conducting an active web session on the webpage, an alert, which may be communicated via the webpage, is generated and communicated to a user in response to determining that there was an unauthorized change.
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
Systems and methods are disclosed for a card device that integrates eSIM technology and Distributed Ledger Technology (DLT) to provide a secure, flexible solution for handling transactions across multiple financial institutions (FIs). The card system associates a single, secure eSIM-enabled card with multiple accounts and FIs, enhancing transaction security and efficiency. The card, embedded with an eSIM, allows dynamic association with customer details and FI accounts, ensuring each transaction is authenticated on a decentralized platform without sharing sensitive information. The system employs DLT for logging transaction details and managing transaction metadata centrally, providing fraud detection and real-time settlement capabilities. The invention improves security by using cryptographic methods and real-time monitoring including geo-locating of cards and clones to prevent unauthorized access and fraud, addressing the need for a secure, multi-institution financial transaction platform.
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
Various aspects of the disclosure relate to verification of data sets used for real-time processes and/or batch processes. A computing platform negotiates, by a first quantum node, a shared key group with at least a second quantum node and calculates an exclusive or (XOR) value of a pair of the first quantum node and the second quantum node. The first quantum service node performs a shared key grouping with the second quantum node and then selects a quantum key relay link between a real-time node and a batch source node. The computing platform selects a corresponding state of all virtual quantum nodes associated with the quantum key relay link and encapsulates a virtual quantum link state between any two quantum service nodes in the quantum network into a database decision engine data file.
Various aspects of the disclosure relate to dynamically determining user access levels to manage access to enterprise information via application programming interfaces (APIs). A neuro-symbolic AI-based assessment enabled system manages assessments and response to API calls to ensure data security of information shared with external sources via the API. This system identifies and analyze access patterns via neural networks and symbolic reasoning to dynamically manage a rule set to determine access levels and corresponding data sub-objects that are built in real time to be shared with an API response message.
Various aspects of the disclosure relate to dynamically determining user access levels to manage access to enterprise information via application programming interfaces (APIs). A neuro-symbolic AI-based assessment enabled system manages assessments and response to API calls to ensure data security of information shared with external sources via the API. This system identifies and analyze access patterns via neural networks and symbolic reasoning to dynamically manage a rule set to determine access levels and corresponding data sub-objects that are built in real time to be shared with an API response message.
A system includes a memory configured to store one or more cyber threat scenarios associated with a software application of a plurality of software applications. The system further includes processors for accessing the one or more cyber threat scenarios, identifying, based on the one or more cyber threat scenarios, an actual cyber threat associated with an execution of the software application in accordance with the current configuration, and, in response, executing a dynamic remote based isolation (RBI) engine configured to perform a dynamic reconfiguration of the software application and the system components in response to the identified actual cyber threat. The dynamic reconfiguration is different from the current configuration of the software application and the system components. The processors further cause the software application to be executed in accordance with the dynamic reconfiguration of the software application and the system components.
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
Virtual machine images may be constantly scanned using background process, to identify current and evolving security risks, such as by optimizing the image scanning a last-in, first-out (LIFO) stack to prioritize most relevant images. Older and/or non-relevant image are removed from the scanning process and removed from use. Virtual machines image prioritization is based on each virtual machine image's current and/or potential usage requirement, where the LIFO stack prioritizes the scanning order. Newly created virtual machine images and/or newly re-activated virtual machine images are placed onto a provisioning queue (first-in, first out) before activation. The virtual machine images active within a host computing environment are processed via a reconciliation process to scan for indications of security vulnerabilities and/or threats to network security. Obsolete or otherwise irrelevant virtual machine images are removed from use via a repository synchronization process.
A system for creating a controllable output summary of text is disclosed. The system generates a set of summaries of text and for a first summary from among the set of summaries, executes a script that is configured to append the first summary to a set of summary-title pairs. The system generates a first title associated with the first summary in response to executing the script. The system compares the first title with the text. Based at least on the comparison, the system determines if the title indicates the context of the text. If it is determined that the title indicates the context of the text, the system generates a dataset of title-text pairs including the first title paired with the text. The system trains a target summarization algorithm with the generated dataset.
An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to receive information parameters associated with a machine learning (ML) model of the one or more ML models and execute an ML algorithm to evaluate the information parameters in accordance with one or more latency classification operations. The one or more latency classification operations are configured to determine whether the ML model comprises multiple latency complications. Further, the processor is configured to generate multiple analysis results indicating that the ML model comprises the latency complications in response to evaluating the information parameters, determine a latency cause of the latency complications based on the analysis results, and determine multiple corrective operations configured to correct the latency cause. The processor is configured to update the ML model to comprise the corrective operations and generate a report configured to release an updated version of the ML model.
Systems, computer program products, and methods are described herein for the systematic splicing of original content into frames and the insertion of blank non-fungible token (NFT) tagged frames at critical points within the multimedia preventing Artificial Intelligent (AI) tool modification of an original multimedia. The invention is configured to prevent content editing using blank NFT token frame insertion, providing NFT integration for all multimedia digitally rendered. Each multimedia frame is associated with a unique NFT, creating a digital fingerprint for authentication. Blank NFT frames are strategically inserted throughout the multimedia based on criticality of the frame to the overall multimedia, forming a grid pattern. The system implements distributed ledger technology where NFT information is stored on a ledger for transparency and immutability. Upon source key recognition replacement frames will replace blank NFT frames in real time through consortium network to render at a releasing entity end point.
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
56.
SYSTEMS AND METHODS FOR DYNAMIC PROTECTION OF WIRELESS COMMUNICATION PROTOCOLS UTILIZING STEGANOGRAPHIC KEYS AND DUAL-LAYER CERTIFICATE AUTHENTICATION
Systems, computer program products, and methods are described herein for dynamic protection of wireless communication protocols utilizing steganographic keys and dual-layer certificate authentication. The present disclosure is configured to identify the type of network to which a user device is connected, determine whether the network is approved, public, or captive, and provide a recommendation to enable wireless protection mode for untrusted networks. The system generates an on-demand protection key via a steganography server and signs it using a wireless protection certificate through a “Key in Key” (KIK) mechanism. The transaction application validates the certificate and encrypts sensitive transaction data using the on-demand key. Only packets that successfully validate the certificate are processed, while others are ignored. This dual-layer authentication prevents unauthorized packet-in-packet attacks and ensures data integrity and confidentiality across various wireless networks.
Aspects related to machine learning-based script interruption handling are provided. A computing platform may train a machine learning model to identify, for a test script interruption, a corrective action to resolve the interruption. The platform may receive information and details corresponding to an interruption associated with a test automation script. The platform may identify, by executing a machine learning model, a cause of the interruption and a predicted corrective to resolve the interruption. The platform may cause, based on identifying the predicted corrective action, initiation of the corrective action. The platform may update, based on the corrective action, the machine learning model. The platform may also resume the test automation script from the point of interruption.
An intelligent and multi-layered approach that uses real-time analysis to identify and confirm the authenticity and inauthenticity of bulk digital documents. Support Vector Machine (SVM) learning is implemented to perform significant attribute validations, such as barcode validation, image-specific validations, and signature validations. An SVM classifier is implemented to compare, analyze, predict the accuracy of the document (i.e., quantify the certainty of authenticity) and decision the documents as either valid/authentic or invalid/tampered-state. Neuro-symbolic Artificial Intelligence (AI) technology is subsequently implemented to confirm or deny the authenticity decision resulting from the SVM classifier.
G06V 20/00 - ScènesÉléments spécifiques à la scène
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p. ex. de formulaires ou de tableaux d’entreprise
G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
59.
MACHINE LEARNING-BASED PLATFORM TO DETECT AND HANDLE VOLUMETRIC ATTACKS
Aspects related to a machine learning-based platform to detect and handle volumetric attacks are provided. A volumetric attack detection and handling platform may train a machine learning model to identify and/or predict volumetric attacks, generate predicted corrective actions, and execute actual corrective actions. The platform may receive information of a network request corresponding to a volumetric attack or a request from a legitimate user. The platform may identify a correlation of volumetric attack and/or legitimate requests using the model. The platform may further identify a predicted corrective action using the model. The platform may cause, based on identifying the predicted corrective, initiation of a response to the malicious traffic request. The response to the malicious traffic request may comprise implementing an actual corrective action generated by the model. The platform may update the machine learning model based on the information of recent requests and corrective actions.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
60.
SYSTEM AND METHOD FOR AUTOMATED TEST CASE GENERATION USING A HYBRID ARTIFICIAL INTELLIGENCE MODEL
A system is provided for automated test case generation using a hybrid artificial intelligence model. In particular, the system may comprise an automated test generator (“ATG”) that may automatically generate test cases or scenarios using one or more artificial intelligence (“AI”) models. In this regard, a user may input a high level test scenario into the ATG. Subsequently, the ATG may use a hybrid model (e.g., a model combining multiple transformer models) to generate complex and comprehensive test cases based on the user input. In some embodiments, the ATG may use an AI accelerator processing unit to increase the speed of the test case generation and refinement processes. In this way, the system provides an expedient, efficient way to generate complex test cases for software testing applications.
A system includes a memory configured to store a set of application environment parameters associated with a software application of a plurality of software applications. The system further includes processors for accessing the set of application environment parameters associated with the software application, identifying, based on the set of application environment parameters, a plurality of potential threats and vulnerabilities associated with an execution of the software application in accordance with the current configuration, and executing one or more generative machine-learning models trained to generate a prediction of one or more cyber threat scenarios based on the set of application environment parameters and the plurality of potential threats and vulnerabilities. The prediction of the one or more cyber threat scenarios includes cyber threat scenarios specific to the software application. The processors further output, by the one or more generative machine-learning models, the prediction of the one or more cyber threat scenarios.
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 11/36 - Prévention d'erreurs par analyse, par débogage ou par test de logiciel
Systems and methods for an integrated, multi-channel, conversational utility are provided. Methods include providing a single search icon on a user device accessing an online portal. Methods include receiving a conversational input inquiry and, via a specially trained ML model, generating a first set of results including at least one general information resource result and at least one user-specific information result. When the first set of results exceeds a threshold confidence score, methods include displaying the first set of results as a response to the input inquiry. When the confidence score fails to exceed the threshold score, methods include generating a conversational follow-up question designed to clarify the intent of the input inquiry, receiving a response to the follow-up question, generating a second set of results and, when the second set of results exceeds the threshold confidence score, displaying the second set of results as the input inquiry response.
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 16/9538 - Présentation des résultats des requêtes
63.
Attribute recharacterization in individual portions of images
An apparatus comprises a memory communicatively coupled to a processor. The processor is configured to generate a tag for a portion of peripheral information, determine a correlation between the peripheral information and the tag and execute a machine learning algorithm in response to determining that an amount of information preserved is outside an accuracy tolerance to determine at least one difference between the peripheral information and the communication information, evaluate the at least one difference against historical data associated with the network device, determine multiple tagging commands based on an evaluation of the at least one difference against the historical data and modify the tag to incorporate the possible modifications, and generate a portion of the communication information based on the portion of the peripheral information in accordance with a modified version of the tag and transmit the portion of the communication information to the network device.
Embodiments of the present invention provide a system for mitigating dual domain vulnerabilities using fiber optic gyroscope and quantum cryptography. The system is configured for receiving an alert associated with misappropriation of an interaction processing device, via a quantum communication channel, in response to receiving the alert, extracting monitoring data associated with the interaction processing device from one or more monitoring devices, analyzing the alert received via the quantum communication channel and the monitoring data extracted from the one or more monitoring devices, determining unauthorized access of the interaction processing device based on analyzing the alert and the monitoring data, and performing one or more actions to mitigate vulnerabilities associated with the unauthorized access of the interaction processing device.
Arrangements for using generative artificial intelligence models for ATM process generation are provided. In some examples, a computing platform may receive, from at least one image or measurement capture device, dimension data associated with an ATM. The ATM may have a plurality of components arranged on a face of the ATM. The dimension data may be input to a generative artificial intelligence model and the model may be executed to output, based on the dimension data, a position or location of each ATM component relative to a reference point on the ATM. In some examples, the model may further output at least one audio script describing the location of each component. The model may output one or more translations of the at least one audio script. The computing platform may transmit or send the at least one audio script to the ATM for presentation during user interaction with the ATM.
G07F 19/00 - Systèmes bancaires completsDispositions à déclenchement par carte codée adaptées pour délivrer ou recevoir des espèces ou analogues et adresser de telles transactions à des comptes existants, p. ex. guichets automatiques
66.
SYSTEM FOR ADVANCED NETWORK TRAFFIC ANALYSIS IN A COMPUTING ENVIRONMENT
Systems, computer program products, and methods are described herein for advanced network traffic analysis in a computing environment. The present disclosure is configured to retrieve, from a traffic data log of a Web Application Firewall (WAF), information associated with a blocked traffic instance; implement, using a code analysis subsystem, a security testing protocol on a host application associated with the blocked traffic instance; determine an exposure associated with the host application based on at least implementing the security testing protocol; generate a notification comprising information associated with the exposure; and transmit a signal configured to cause a computing device associated with the host application to display the notification.
A computing platform may train, using historical telemetry state images, an image comparison model to identify matches between telemetry state images. The computing platform may generate a plurality of system alerts corresponding to a period of time. The computing platform may access telemetry data corresponding to the period of time. The computing platform may generate, based on the telemetry data and for a time corresponding to each of the plurality of system alerts, a telemetry state image. The computing platform may input, into the image comparison model, the telemetry state images to identify whether or not any of the plurality of telemetry state images match. Based on detecting a match, the computing platform may consolidate system alerts corresponding to the matching telemetry state images, which may produce a single system alert and may send, to a user device, the single system alert.
G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G08B 21/00 - Alarmes réagissant à une seule condition particulière, indésirable ou anormale, et non prévues ailleurs
68.
NON-LINEAR DATA DEPENDENCY DETECTION IN MACHINE LEARNING USING HYBRID QUANTUM COMPUTING
Methods for detecting non-linear data dependencies in machine learning using hybrid quantum computing. Methods include receiving a selection of an accuracy metric. Methods include receiving a data set comprising a plurality of data elements for processing by a machine learning model operating on a machine learning system. Methods include identifying a plurality of data elements within each data set. Methods include identifying one or more features for each data element. Methods include determining a total number of features for the data set. Methods include reducing, by a quantum annealing method, based on the accuracy metric, the total number of features to a reduced number of features. Methods include inputting the reduced number of features into the machine learning model. Methods include outputting a result from the machine learning model.
G06N 10/80 - Programmation quantique, p. ex. interfaces, langages ou boîtes à outils de développement logiciel pour la création ou la manipulation de programmes capables de fonctionner sur des ordinateurs quantiquesPlate-formes pour la simulation ou l’accès aux ordinateurs quantiques, p. ex. informatique quantique en nuage
H04L 51/02 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
69.
STORED VALUE PAYMENT INSTRUMENT, HAVING PAYMENT CARD CHARACTERISTICS, FOR VIRTUAL CASH TRANSACTIONS
A method for transferring goods from a digital+bitcoin (d+b) stored value transaction instrument-supporting vendor to a user device, or a device user, such as a d+b stored value transaction instrument is provided. The device may be registered with a cryptocurrency provider and a value allocation. The method may include receiving a user request configured for a cryptocurrency-based transaction; transmitting a consent to transact the cryptocurrency-based transaction and, in response to the transmitting, receiving, from the user device, a Quick Response (QR) code. The code specifies, at least: a) an amount of cryptocurrency; and b)
a product or a service to be exchanged for the amount of cryptocurrency. The method may also receive a biometric characteristic that confirms the transaction. The method may then receive the amount of cryptocurrency via the d+b stored value transaction instrument, and transmit a confirmation of receipt of the cryptocurrency.
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
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
70.
Generative Artifical Intelligence-Based Automated Teller Machine Process Generation
Arrangements for using generative AI models for ATM process generation are provided. A computing platform may receive user input from an ATM and may identify, based on the user input, a first generative AI model associated with a first functionality of the ATM. The platform may execute the first model to output a preferred language and a first plurality of options in the preferred language. The platform may generate and transmit, to the ATM, a first output providing the first plurality of options. In response, the ATM may receive second user input selecting an option of the first plurality of options. The platform may identify a second generative AI model associated with second functionality of the ATM. The platform may execute the second model to output a second plurality of options. The platform may generate and transmit, to the ATM, a second user output including the second plurality of options.
G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
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
Systems, computer program products, and methods are described herein for determining electronic activity using advanced computational models for data analysis and automated processing. The present disclosure is configured to generate a criticality assessment of a task based on one or more weights determined by an impact analysis; allocate a grant token to the task, wherein the grant token comprises an allotment of processing time of the system to complete the task; monitor execution of the task, wherein monitoring the execution comprises comparing an execution timeframe, wherein the execution timeframe comprises an amount of processing time to execute the task, and an execution timeframe factor, wherein the execution timeframe factor is a multiple of the processing time allocated by the grant token; and terminate a malicious task, wherein terminating the malicious task comprises flagging the malicious task and terminating completion of the malicious task.
Systems, computer program products, and methods are described herein for altered data generation and transient use via electronic arrangement protocols. The present disclosure includes retrieving data of a first database, aggregating the data with additional data to form an aggregated data object, tagging the aggregated data object with at least one summary tag, searching an electronic arrangement protocol repository to identify at least one electronic arrangement protocol related to the at least one summary tag, wherein the at least one electronic arrangement protocol may include a first electronic arrangement protocol rule, for a first element of the at least one summary tag, comprising instructions to alter identifiable information, fabricating synthetic data based on the aggregated data object using the at least one electronic arrangement protocol, generating and appending the non-fungible token to a distributed ledger.
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
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
73.
Secure Storage and Distribution of Docker Images using Homomorphic Encryption and Blockchain
Arrangements for securely storing and distributing docker images are provided. A computing platform may receive a docker image. The computing platform may scan the docker image. The computing platform may generate a CVE list based on identified vulnerabilities and incorporate the CVE list into the docker image. The computing platform may encrypt the docker image and send the docker image to a docker image storage system. The computing platform may create an image BCID and encrypt the image BCID. The computing platform may generate and record metadata associated with the image BCID on a blockchain network.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
H04L 9/06 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité l'appareil de chiffrement utilisant des registres à décalage ou des mémoires pour le codage par blocs, p. ex. système DES
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
A system for protecting source code from unauthorized access is disclosed. The system is configured to scan the source code and identify code segments, including function code. The system may perform code obfuscation, code separation, and code encryption. The system may extract a first set of code features from the function code. The first set of code features indicates a first task associated with the function code. The system accesses a training dataset comprising a sample code that is associated with a second task and a template code. The system compares the first task with the second task. In response to determining that the first task corresponds to the second task, the system obfuscates the function code with the template code. In response, the system updates the source code to include the obfuscated function code.
Embodiments of the present invention provide a system for identifying and redirecting incoming unauthorized data access requests. The system is configured for continuously monitoring one or more incoming data access requests from one or more sources, identifying that a data access request of the one or more incoming data access requests is an unauthorized request, redirecting the data access request to a controlled environment, performing one or more actions in the controlled environment to capture one or more interactions associated with the data access request within the controlled environment, and automatically generating one or more controls to secure a real-time environment based on the one or more interactions captured within the controlled environment.
G06F 21/53 - 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 au stade de l’exécution du programme, p. ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p. ex. "boîte à sable" ou machine virtuelle sécurisée
G06F 21/45 - Structures ou outils d’administration de l’authentification
76.
SECURE VALIDATION OF SPATIAL COMPUTING DATA TRANSMITTED OVER SPINE-LEAF NETWORK USING HOMOMORPHIC SERPENT CRYPTOGRAPHIC ALGORITHM
A method for validating a data transmission pathway between two organizations across a spine-leaf network may use two cryptographic algorithms to validate the pathway. Data used to validate the pathway may include spatial computing telemetry. Once validated, sensitive data may be transmitted over the pathway. The spine-leaf network may receive one hash value encrypted by a homomorphic encryption algorithm run by an organization and another hash value encrypted by a serpent encryption algorithm run by a separate organization. A processor running in the spine-leaf network may validate an integrity of the data transmission pathway by comparing the two hash values to see if they are equivalent. When the hash values are equivalent, the pathway may be validated, and the sensitive data may be transmitted between the two organizations. The sensitive data may be transmitted as ciphertext. The sensitive data may include spatial computing telemetry.
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
G06F 21/64 - Protection de l’intégrité des données, p. ex. par sommes de contrôle, certificats ou signatures
77.
Detecting Fraudulent Optical Tone Transactions Received by Client Using Spiking Neural Network and Quantum Sensors
Systems and methods secure transactions using optical tones, which are audio or visual signals encoded with transactional data, combined with advanced security measures. It employs Quantum encryption to initially secure the optical tones at creation, ensuring their integrity and confidentiality. During a transaction, spiking neural networks (SNNs) process these encrypted tones, filtering out irrelevant or harmful data and authenticating the content. Concurrently, Quantum sensors analyze the electromagnetic properties of the tones, such as frequency and pitch, to detect any signs of tampering or forgery. If discrepancies are found, the transaction is halted to prevent fraud. This invention also supports dynamic security management, allowing for on-demand updates to encryption parameters and the generation of new tones as needed. Additionally, for higher-value transactions, multiple tones may be required, enhancing the security framework. This invention offers a robust solution to secure optical tone-based financial transactions against advanced fraudulent activities.
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
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
A system for implementing code changes comprises a code repository that stores replacement lines of code that each have a relevancy ranking and a safety ranking. The system is configured to receive a notice from an external source hosting an application that a previous set of code associated with the application needs to be changed. The system then identifies a new set of codes from the code repository with high relevance and safety values. It implements a virtual secured environment that simulates the application with the identified new set of code and one or more other external source components. Feedback is then received from the virtual secured environment and recorded in a log. The new set of code is then sent to the external source for implementation when the feedback does not indicate a failure.
A method for monitoring transactions for identifying fraudulent activity is provided. The method may include receiving a transaction request at a payment switch interface from a payment network. The method may include comparing the transaction request to all transactions received that are within a predetermined time immediately preceding a timestamp of the time of execution of the transaction request and that include a geolocation that is within a predetermined proximity to the geolocation of the transaction request. In response to the comparing, the method may include identifying a number of transactions greater than a first threshold that are received within the predetermined time and the geolocation is within the predetermined proximity. Following the identifying, the method may include executing a geofencing by restricting transactions from being executed via the smart card and a plurality of smart cards associated with the payment network that are being executed from within the geolocation.
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
G06Q 20/34 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des cartes, p. ex. cartes à puces ou cartes magnétiques
80.
SYSTEM AND METHOD FOR ORCHESTRATION OF MOBILE EXCHANGE UTILIZING DECENTRALIZED NON-FUNGIBLE TOKEN IDENTIFICATION AND SECURE NEAR-FIELD COMMUNICATION
Systems, computer program products, and methods are described herein for the orchestration of mobile exchange utilizing decentralized non-fungible token identification and secure near-field communication. The invention enables a device to manage a series of operations including receiving transaction requests via a customer application, activating a teller selection algorithm, and generating necessary notifications for transaction management. The system handles secure exchanges of physical funds through near-field communication, reinforced by the generation of unique transaction IDs and public keys for enhanced security. Additionally, all transaction details are meticulously recorded on a distributed ledger, ensuring the integrity and traceability of each transaction.
Embodiments of the present invention provide a system for dynamically performing resource upgrades based on determining change windows via a generative artificial intelligence engine. The system is configured for collecting one or more records associated with entity resources and store the one or more records in a data warehouse, receiving a resource upgrade request associated with a first entity resource, generating one or more change windows to implement the resource upgrade request, via a generative Artificial Intelligence engine, selecting a change window of the one or more change windows based on the prediction score, implementing the resource upgrade request during the change window, performing validation of the implementation of the resource upgrade request, and generating and transmitting one or more notifications associated with the validation to one or more users associated with a set of entity resources linked with the resource upgrade request associated with the first entity resource.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
82.
AUTOMATED VISHING DETECTION TO PREVENT DEEPFAKE AND CHATBOT ATTACKS
A computing platform may train, using historical call information, a prompt generation model to identify, for an initiated call between a first individual and a second individual, one or more security prompts to validate an identity of the first individual. The computing platform may detect and temporarily pause a call. The computing platform may input, into the prompt generation model, information of the call, which may cause the prompt generation model to output the security prompts, which may be customized CAPTCHA tests based on the information. The computing platform may send, while the call is paused and to a user device of the first individual, the security prompts. The computing platform may receive, while the call is paused and from the user device, responses to the one or more security prompts. The computing platform may validate, while the call is paused, the responses, and resume the call.
A method for enabling continuity of access to a primary dataset stored in a computer network is provided. The method utilizes a node, a computer processor, and non-transitory computer-readable media storing computer-executable instructions. The node is connected to the computer network. The method includes configuring the mobile device for wireless connection to the computer network. The method includes configuring the mobile device to receive indication that the node is disconnected from the computer network and transmit a copy of the primary dataset or a portion thereof from the computer network to the node. The method includes configuring the node to enable operations on the dataset copy and keep a record of them. The method includes configuring the node to receive indication that the node is connected to the computer network and transmit the record to the computer network.
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 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
A method includes receiving a suspicious text message having information data, and applying a hashing function to the information data to generate hashed information data. The method includes storing the hashed information data in one or more of a plurality of network nodes in a blockchain network, and determining that at least a portion of the information data associated with the suspicious text message contains malicious data based at least in part upon known hashed malicious data.
A method includes intercepting requests, which are analyzed to identify authenticated and suspicious requests. The suspicious requests are grouped into request groups based on respective geolocation information. A rate of requests is determined for a request group. In response to determining that the rate of requests is less than or equal to a request rate threshold, parameters of a suspicious request of the request group are analyzed to determining values of the parameters. In response to determining that the value of the parameters do not match with respective malicious parameter values stored in a block list, the suspicious request is analyzed using a neural network to identify if the suspicious request is legitimate or malicious. In response to identifying that the suspicious request is malicious, a notification indicating that the suspicious request is identified as malicious is sent, and the values of the parameters are added to the block list.
SYSTEM FOR TRACKING THE CONTROLLING ENTITY OF INTERNET PROTOCOL (IP) ADDRESSES AND IMPLEMENTING SECURITY THREAT MITIGATION BASED ON THE CONTROLLING ENTITY
Systematically verifying the identities of entities in control of Internet Protocol (IP) addresses and determining a security threat status for each of the entities based at least on the verified identity. As incoming data packets are received from an originating IP address, the entity in control of the originating IP address and their corresponding security threat status are identified and data packets are dispositioned i.e., blocked/dropped, sequestered or authorized for further transmission, based on the security threat status of the entity in control of the IP address.
Arrangements for continuous authentication and secure access control are provided. In some aspects, a computing platform may receive user data from a plurality of user data sources. The user data may include a plurality of different data types. The computing platform may use the user data to train a machine learning model, which may then be used to generate user specific baseline data. Subsequent user data may be received and analyzed, using the machine learning model, to determine whether an anomaly exists between the subsequent user data and the baseline data. If not, the user may be considered authenticated and second user data may be received and analyzed to continuously authenticate the user. If an anomaly is detected, the anomalous data and other data may be further analyzed to determine whether to authenticate the user or execute a response action.
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
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
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
88.
SYSTEMS, METHODS, AND APPARATUSES FOR GENERATING RESOURCE TRANSMISSIONS USING SATELLITE-BASED COMMUNICATIONS
Systems, computer program products, and methods are described herein for generating resource transmissions using satellite-based communications. The present invention is configured to identify a user device, wherein the user device comprises a satellite-based communication component; generate, by the user device, a resource transmission request; determine, based on the satellite-based communication component, a satellite-based communication transmission volume; generate, based on the satellite-based communication transmission volume, a resource transmission satellite communication, wherein the resource transmission satellite communication comprises at least a portion of the resource transmission request; transmit, via a satellite component, the resource transmission satellite communication to a resource transmission processing component; and allow, in an instance where the at least one resource account meets the resource transmission request, the resource transmission request.
Various aspects of the disclosure relate to distributed ledger computing systems and customizing tokens for securing and facilitating transactions recorded in the distributed ledger. A token customization module may be used to build customized controls into a token for use in a blockchain system. The token customization module may personalize or otherwise customize rules based on requirements of a user's particular use of the distributed ledger system. The customized rules may be used to trigger alerting behavior, prevent and/or automate particular transactions, provide geofencing and/or regional restrictions for transactions of a specified type, among others. Once built, the rules may be incorporated into the tokens and immutably memorialized in the distributed ledger. The customized tokens may be associated with or incorporate a smart contract to layer additional functionality.
Systems, methods, and computer program products are provided herein for data trace and sequence determinations in distributed networks. An example method includes receiving a request for an interaction determination and determining a plurality of distributed service systems associated with the interaction. The plurality of distributed service systems include a sequence defining an order by which operations associated with the interaction are performed by respective distributed service systems and each of the distributed service systems includes trace agents that generate service system specific data trace objects. The method further includes capturing the one or more service system specific data trace objects for each of the distributed service systems and generating an interaction object based on the service system specific data trace objects for each of the distributed service systems associated with the interaction.
Intelligent secure methods, processes, systems, and apparatus are disclosed for controlling and monitoring volatile memories in third-party vendor systems, such as an ATM or PoS, providing a solution to track and integrate memory components into the monitoring system of a customer's financial institution using scanning procedures, homomorphic encryption, and blockchain transactions to establish trust and ensure confidentiality by orchestrating the coupling of distributed memory storage located on the third-party vendor systems and/or hardware by leveraging PCCO (Parity Check Control Object) and DIP (Dependency Inversion Protocol).
A computing platform may receive matrix multiplication information indicating a plurality of matrix dimension sets for matrix multiplication. For each matrix dimension set, the computing platform may: 1) identify one or more multiplication variations, indicating different possible orders of operation for executing the corresponding multiplication, 2) perform memoization to identify, for each order of operation, a corresponding number of operations to complete the corresponding multiplication, 3) identify, based on the numbers of operations, a most efficient order of operation, and 4) store, in a lookup table, a relationship between the given matrix dimension set and the most efficient order of operation. The computing platform may identify matrix dimensions for a model configuration request, and identify, using the lookup table, a corresponding order of operations. The computing platform may iteratively train the generative AI model based on the order of operations, and deploy the generative AI model.
Aspects related to protecting data privacy using data-masking labels in systems providing request fulfillment by consortium are provided. A request fulfillment platform may train an analysis model to output smart contracts. The platform may receive an event processing request. The platform may identify a label corresponding to the event processing request. The platform may authenticate the event processing request based on the label. The platform may identify parameters of the event processing request based on information of a market corresponding to the event processing request. The platform may generate a complexity score for the event processing request based on inputting the label into the analysis model. The platform may generate an indication of whether fulfillment of the event processing request requires a consortium based on the complexity score. The platform may generate smart contracts based on the indication. The platform may send the smart contracts to a device.
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
94.
SYSTEMS AND METHODS FOR DYNAMICALLY GENERATING AND MAPPING UNICODE FOR CROSS-DISTRIBUTED NETWORK DATA TRANSMISSIONS
Systems, computer program products, and methods are described herein for generating and mapping unicode for cross-distributed network data transmissions. The present disclosure is configured to identify a cross-distributed network data transmission comprising source ledger code; generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission; generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM); generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger; convert the source ledger code to a unicode; receive, by a receiver schema mapping module, the unicode and the code mapping instructions; and generate, by the receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions.
Digital payment systems and methods leveraging optical tones, blockchain technology, and neuromorphic computing to enhance transaction security and flexibility are disclosed. By initiating transactions with unique optical tones generated through mobile IoT applications, payment instructions are encoded into visually encrypted signals, ensuring high security from the outset. Multi-Factor Authentication (MFA), including advanced facial recognition via Convolutional Neural Networks (CNNs), authenticates users, while Spiking Neural Networks (SNNs) process and filter the optical tones, focusing on pertinent transaction details. The system utilizes blockchain oracles and smart contracts for validating transactions and automating the execution of payment instructions, respectively. A novel aspect of this invention is the ability to generate custom payment tokens, either embedded within optical tones or as separate entities, to facilitate specific transactions. This approach not only significantly enhances the security of digital payments but also introduces unprecedented flexibility in managing financial transactions, setting spending limits, and executing recurring payments.
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
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
96.
ENCRYPTION-AWARE VERIFICATION TOKENS FOR USE IN A DECENTRALIZED DATA SYSTEM
Embodiments of the invention relate to systems, methods, and computer program products for encryption-aware verification in a decentralized network, the invention including encrypting a message at a first node; generating a first encryption-aware verification token (“EAT”) associated with the message; performing a first encryption-aware verification process at a second node; verifying the first EAT; and decrypting the message. In some embodiments, the invention further includes generating a second EAT at the second node; performing a second encryption-aware verification process at a third node; verifying the second EAT; and decrypting the message at the third node.
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
97.
System and method for securing user data against internal cyber threats
A system includes a memory configured to store user profile data associated with a user, user interaction data associated with a preauthorized user, and a software application configured to access the user profile data. The system further includes processors configured to access the user interaction data, in which the user interaction data is captured in relation to a natural language exchange session. The processors execute a generative machine-learning model trained to identify an intent of the preauthorized user based on the user interaction data associated with the preauthorized user, determine, based on the identified intent, whether the user interaction data corresponds to a sequence of authorized user interactions or a sequence of unauthorized user interactions, and, in response to determining that the user interaction data corresponds to the sequence of unauthorized user interactions, cause the software application to restrict access of the preauthorized user to the user profile data.
The present invention introduces an advanced system and method for predictive maintenance and fault detection, leveraging the synergistic potential of quantum computing and graph transformer networks. This innovation collects and preprocesses data from diverse sources through edge computing, enriching this data with supplemental information to construct a comprehensive operational dataset. Utilizing an ontology-based framework, the system organizes the data into a knowledge graph, which is then analyzed using quantum computing techniques to uncover complex, correlated relationships. The extracted relationships are further analyzed by a Graph Transformer Network (GTN) equipped with a multi-head attention mechanism, enabling the identification of spatio-temporal patterns indicative of potential system faults. The system classifies these patterns to distinguish between normal operation, potential faults, and outliers, facilitating proactive maintenance actions. This invention represents a significant advancement in the field of predictive maintenance, offering improved reliability, efficiency, and operational insight for complex systems.
Intelligence acquisition is conducted via conversational interactions and micro-credential competency logic. An AI system including ML models are trained to generate segments associated with at least one subject matter and determine which of the segments to present to a user and/or assess a level of competency of the user in the subject matters associated with the segments. A learning application identifies the user and, in response, receives characteristic data and/or historical learning data associated with the user. In response, the learning application determines, using the ML models, the segment(s) to present to the user based, at least, on the characteristic data and/or historical learning data. Once the determined segments are presented, the learning application conducts a series of conversational interactions with the user using the artificial intelligence system and assesses the level of competency of the user in subject matter(s) associated the presented segment.
An acoustic fingerprinting system includes an initial request from an authentic user. The input comprises a password with a plurality of keys. A smart sensor measures sounds associated with the keys. The smart sensor converts the sounds into notes that correspond to the keys. The notes may be stored in a database. There may be a second request from a user to access the system. The second request may include a second input of the password. The second input may include a sound associated with the keys of the password. The sounds may be converted to second notes. The second notes may be compared to the notes stored in the database. The user may be assigned a score based on the comparison. In the event that the score is greater than a predetermined number, the user may be granted access to the system.
G06F 21/40 - Authentification de l’utilisateur sous réserve d’un quorum, c.-à-d. avec l’intervention nécessaire d’au moins deux responsables de la sécurité
G06F 21/32 - Authentification de l’utilisateur par données biométriques, p. ex. empreintes digitales, balayages de l’iris ou empreintes vocales
