A method is disclosed. The method includes receiving, by a server computer from a user device comprising a transfer application via a communications network, contact data for a plurality of potential users on the user device. The method also includes searching, by the server computer a database, for a set of aliases associated with the potential users in the contact data. The method also includes providing, by the server computer via the communications network, the set of aliases to the user device. The user device is programmed to store the set of aliases in the transfer application, receive a selection of an alias associated with a user, and initiate an interaction with the alias using the transfer application.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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
2.
AUTHENTICATION SYSTEMS AND METHODS USING LOCATION MATCHING
A method is disclosed. The method includes receiving, by a token server from an application provider computer, a request to obtain a token for a transaction. The request to obtain the token comprising sensitive information and a transaction identifier. The method further includes retrieving, by the token server, the token, and receiving, by the token server from a resource provider computer, a request for the token, the request for the token comprising the transaction identifier. The method also includes providing, by the token server to the resource provider computer, the token.
A computer generates a cryptographic puzzle and a puzzle tag based on a private verification key, a secret, and a public traceability key. The computer provides a first interaction request message comprising the cryptographic puzzle and the puzzle tag to a first device. The first device or a second device modifies the cryptographic puzzle to obtain a modified cryptographic puzzle, a random value, and a traceability token. The computer receives a second interaction request message comprising the modified cryptographic puzzle and the traceability token from the second device. The computer verifies the modified cryptographic puzzle. The computer solves the modified cryptographic puzzle to obtain a modified secret and provides a second interaction response message comprising a modified puzzle solution or indication thereof to the second device. The second device or the first device, modifies the modified secret using the random value to obtain the secret.
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
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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
4.
METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR ORTHOGONALLY ENCODING FEATURES IN A LEARNED VECTOR REPRESENTATION
Methods, systems, and computer program products for orthogonally encoding features in a learned vector representation are provided. An example method may include allocating a first plurality of coordinates of a latent vector embedding of a machine learning model, orthogonally encoding a plurality of features corresponding to one or more labels of a first plurality of labels associated with a classification task in the first plurality of coordinates of the latent vector embedding, training the machine learning model based on a training dataset to provide a trained machine learning model that comprises an augmented latent vector embedding, wherein the training dataset comprises a plurality of data points having a second plurality of labels, and wherein the first plurality of labels is included in the second plurality of labels, and performing one or more classification tasks based on the augmented latent vector embedding.
Provided are methods that include receiving an initial training dataset, where each data instance of the initial training dataset has a label and a first percentage of the plurality of data instances are labeled correctly, providing the initial training dataset as an input to a reinforcement learning agent (RLA) machine learning model to generate a second training dataset, where a second percentage of data instances of the second training dataset are labeled correctly and the second percentage is greater than the first percentage, training a deep learning model using the second training dataset to provide a trained deep learning model, testing the trained deep learning model using a testing dataset to generate a resultant dataset that has a detection rate, which is an indication of a number of data instances that were predicted correctly, and generating a reward parameter. Systems and computer program products are also disclosed.
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 and methods include establishing a communication session between a user computing device and a mobile device of a user; receiving, by the user computing device from the mobile device, a token, wherein the token is received by the mobile device after the mobile device transmits a credential obtained from a portable device of the user to a token service computer; and transmitting, by the user computing device, the token to a resource provider computer, which generates and transmits an authorization request message comprising the token to a processing network computer for authorization.
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 transaction card includes card information, and a card face with a selectively modifiable transparency, wherein the card face is selectively switchable between a first state characterized by a first transparency and a second state characterized by a second transparency less than the first transparency, and wherein the card information is visible in the first state and obscured in the second state.
Systems, methods, and computer program products for dynamic passcode communication use a merchant application installed on a user device that receives transaction data associated with a transaction at a merchant system. The transaction data may include an account identifier associated with an account at an issuer system. The merchant application determines, based on the account identifier, whether an issuer application associated with the issuer system is installed on the user device. In response to determining that the issuer application is installed on the user device, the merchant application transmits, to the issuer application, a request for a dynamic passcode. The merchant application receives, from the issuer application, the dynamic passcode and transmits, to the issuer system, an authorization request including the account identifier and the dynamic passcode. The merchant application receives, from the issuer system, an authorization response authorizing or denying the transaction.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
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 20/42 - Confirmation, p. ex. contrôle ou autorisation de paiement par le débiteur légal
A computer-implemented method is disclosed. The method includes using a payment network to receive a transmission from a risk-screening module, generate an authentication message based on a prescreened status of the payment network, transmit a communication to the risk-screening module, receive from an acquirer an authorization request for the payment transaction where the authorization request is by the merchant, receive from an acquirer the authentication message, detect the prescreened status of the payment transaction, and associate the authorization request with an indicator of the prescreened status of the payment transaction based on the authentication message. The transmission includes a request for the authentication message for a payment transaction with a merchant associated with the risk-screening module. The payment transaction includes the prescreened status. The communication includes the authentication message. The detecting of the prescreened status of the payment transaction is based on the authentication message.
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
10.
TECHNIQUES FOR MULTI-TIERED DATA STORAGE IN MULTI-TENANT CACHING SYSTEMS
Embodiments of the invention are directed to systems and methods for utilizing a multi-tiered caching architecture in a multi-tenant caching system. A portion of the in-memory cache may be allocated as dedicated shares (e.g., dedicated allocations) that are each dedicated to a particular tenant, while another portion of the in-memory cache (e.g., a shared allocation) can be shared by all tenants in the system. When a threshold period of time has elapsed since data stored in a dedicated allocation has last been accessed, the data may be migrated to the shared allocation. If data is accessed from the shared allocation, it may be migrated back to the dedicated allocation. Utilizing the techniques for providing a multi-tiered approach to a multi-tenant caching system can increase performance and decrease latency with respect to conventional caching systems.
G06F 12/0811 - Systèmes de mémoire cache multi-utilisateurs, multiprocesseurs ou multitraitement avec hiérarchies de mémoires cache multi-niveaux
G06F 12/084 - Systèmes de mémoire cache multi-utilisateurs, multiprocesseurs ou multitraitement avec mémoire cache partagée
G06F 12/0891 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p. ex. mémoires cache utilisant des moyens d’effacement, d’invalidation ou de réinitialisation
Disclosed herein is a service provider system and method to generate a persona token for a user, store the persona token at a restricted access database, and return a persona token identifier to the user. The persona token is used to generate persona insights, that can be provided to an artificial intelligence / machine learning algorithm along with an inquiry. The algorithm may identify goods or services based on the persona insights. Also disclosed herein are system and methods to attribute a user clicking on a product link, retaining and using the product information to link item level details to purchases, and making a purchase on the linked e-commerce / merchant website such that the originating website knows that a purchase ultimately resulted from the clicked ad.
Embodiments provide for a method of allowing for communication between a portable device comprising a portable device NFC antenna and a user device comprising a user device NFC antenna using a bridge apparatus comprising a large coil, a small coil, and an amplifier circuit electrically coupling the large coil and the small coil. The method includes the small coil in the bridge apparatus receiving a near field communication (NFC) signal from the user device NFC antenna. The amplifying circuit can amplify the NFC signal to obtain an amplified NFC signal. The large coil in the bridge apparatus can transmit, to the portable device NFC antenna, the amplified NFC signal.
G06K 7/10 - Méthodes ou dispositions pour la lecture de supports d'enregistrement par radiation électromagnétique, p. ex. lecture optiqueMéthodes ou dispositions pour la lecture de supports d'enregistrement par radiation corpusculaire
H01Q 1/22 - SupportsMoyens de montage par association structurale avec d'autres équipements ou objets
H01Q 1/36 - Forme structurale pour éléments rayonnants, p. ex. cône, spirale, parapluie
Described herein is a biometric identification technique that includes a gateway computer receiving a first set of encrypted match scores and a set of enrollment biometric template identifiers associated with the first set of encrypted match scores from a first database server. The first set of encrypted match scores are decrypted to obtain a first set of match scores, and a subset of enrollment biometric template identifiers of the set of enrollment biometric template identifiers is determined based on a subset of match scores in the first set of match scores. The subset of enrollment biometric template identifiers is transmitted to a second database server, wherein the second database server is programmed to compare a second encrypted reference biometric template to encrypted enrollment biometric templates corresponding to the subset of enrollment biometric template identifiers and generate a second set of encrypted match scores.
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
Disclosed herein is a system and method of biometric reference indexing for identification. The method includes obtaining a set of enrollment biometric references, partitioning the set of enrollment biometric references along a plurality of hyperplanes, each partition being assigned an index address and an indexing function associated with the partition. The indexing function being used to compute an index address of each enrollment biometric reference, the index address pointing to a location on a secure storage device. The method also includes distributing the indexing function to one or more biometric capture devices.
A processing network computer may leverage secure data for customizing (e.g., personalizing) interactions for an account holder. The processing network computer may analyze the secure data using a machine learning algorithm to generate embeddings. The embeddings can anonymize the secure data and be used to generate recommendations customized to the account holder. The generated embeddings and recommendations may be applied to in-person or e-commerce interactions to obtain a set of customizations for the account holder (e.g., customized content on terminal screen, customized content on merchant website).
Methods and systems for using a mobile device as a point-of-sale (POS) terminal provisioned by a resource provider are provided. A server computer can transmit, to a resource provider computer, a set of platform-specific scripts to be incorporated into a resource provider application provisioned on a user device. The server computer can register each instance of the resource provider application provisioned on any user device as an access terminal associated with the resource provider computer. The server computer can receive, directly from an instance of the resource provider application on a user device, a processing request message to perform a transaction. The server computer can obtain an authorization decision on behalf of the resource provider computer and transmit the authorization decision to the user device and the resource provider computer.
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 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
Described herein is a biometric identification technique that includes a gateway computer receiving a first set of encrypted match scores and a set of enrollment biometric template identifiers associated with the first set of encrypted match scores from a first database server. The first set of encrypted match scores are decrypted to obtain a first set of match scores, and a subset of enrollment biometric template identifiers of the set of enrollment biometric template identifiers is determined based on a subset of match scores in the first set of match scores. The subset of enrollment biometric template identifiers is transmitted to a second database server, wherein the second database server is programmed to compare a second encrypted reference biometric template to encrypted enrollment biometric templates corresponding to the subset of enrollment biometric template identifiers and generate a second set of encrypted match scores.
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 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
18.
Combined electronic device and display screen or portion thereof with graphical user interface
Systems, methods, and computer program products are provided for enhancing machine learning model performance without altering the model or acquiring additional data. An example method includes inputting a data set to a first machine learning model to generate predicted labels. Incorrectly labeled data from the data set is identified based on comparing the predicted labels with known labels. A second machine learning model is trained based on the incorrectly labeled data, the predicted labels associated with the incorrectly labeled data, and the known labels associated with the incorrectly labeled data to generate a score associated with accuracy. Synthetic data is generated based on the data set. The first machine learning model is refined based on the synthetic data, synthetic predicted labels associated with the synthetic data generated by the first machine learning model, and scores associated with the synthetic predicted labels generated by the second machine learning model.
Embodiments are directed to methods and systems for crypto-agile encryption and decryption. A computer system can possess a protocol file that identifies one or more cryptographic software modules. Using these cryptographic software modules, the computer system can generate a plurality of shared secrets and a session key, then use the session key to encrypt a message. The message can be sent to a server computer that can subsequently decrypt the message. At a later time, the protocol file can be updated to identify a different set of cryptographic software modules, which can be used to encrypt messages. Further, the server computer can transmit additional cryptographic software modules to the computer system, enabling the computer system to use those cryptographic software modules to generate cryptographic keys. As such, the cryptographic protocol file can be changed in response to changes in the cryptographic needs of the computer system.
A method is disclosed. The method includes receiving, from a user device storing a private key of a public-private key pair, a first attestation message comprising a first attestation data packet, the public key, a user device identifier for the user device, and a credential. The method also includes binding the credential to the user device identifier, and transmitting, to a token service computer, the first attestation data packet. The token service computer previously bound a first token from a first token requestor interacting with the user device to the user device identifier. The method includes receiving, from a second token requestor interacting with the user device, a second attestation message comprising a second attestation data packet, verifying, the second attestation data packet using the public key, and transmitting, verification data to the second token requestor. The second token requestor transmits the verification data to the token service computer.
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
Systems and methods are provided to enable a user to conduct a transaction using their credentials stored on a secure server computer (e.g., a computer associated with a partner such as another merchant) by merely presenting their authentication data at a physical location via an auxiliary device. An auxiliary device may be provided for interfacing with a partner's backend server (e.g., the secure server computer). In some embodiments, biometric authentication may provide a mechanism for a true seamless and potentially frictionless (in the case of modalities that do not require physical contact) interaction. Payment can occur without any need for a card, phone, wearable, or any other user device as long as the auxiliary device is able to recognize the user and retrieve a credential that can be linked to that user.
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/20 - Systèmes de réseaux présents sur les points de vente
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
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 method includes a user device generating a detection secret set (Π). The user device obtains a user credential (η) from a user of the user device. The user device determines a real secret (η∗) based on the detection secret set (Π) and the user credential (η). The user device stores the real secret (η∗). The user device provides the detection secret set (Π) and a backup account identifier (aid) for an account associated with the user to a server computer.
A method is disclosed. The method includes receiving, by a processing system, an enrollment message from a user device operated by a user via an authorizing entity computer. The enrollment message specifies one or more preferences associated with value portions associated with interactions conducted by the user. The method also includes receiving authorization request messages associated with a plurality of interactions conducted by the user, aggregating value portions associated with the authorization request messages to form an aggregate value; and processing a transfer of the aggregate value to one or more records associated with one or more receiving entities.
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 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
A method includes receiving, from a user, a request for an interaction with a resource provider. The request includes a resource provider identifier. The method includes transmitting, to an alias directory, a resolve request message comprising the resource provider identifier and a sending entity identifier, and receiving, from the alias directory, a resolve response message having a token associated with an account of the resource provider managed by a receiving entity, and a key. The key is derived from a plurality of data elements associated with the interaction. The method also includes transmitting, to a user device operated by the user, the key, and transmitting to a receiving entity computer via a processing network, an interaction request message with the token and the key. The key is provided to a resource provider. The user obtains a resource by presenting the key to the resource provider.
In some embodiments, a malware detection system includes an attack channel removal unit, a feature extraction unit coupled to the attack channel removal unit, and a graphical encoding unit coupled to the feature extraction unit and a malware detection unit. In some embodiments, based upon graphically-encoded component-based features and monotonic features extracted from attack-channel-free software output by the attack channel removal unit, the malware detection unit detects malware in software input into the malware detection system. In some embodiments, the monotonic features extracted from the attack-channel free software and the graphically-encoded component-based features are combined to generate a combination monotonic-component based feature vector. In some embodiments, the combination monotonic-component based feature vector is used to detect malware using the malware detection system.
Systems and methods are for performing a secure exchange of encryption keys (e.g., public keys) between two devices. One or more initialization keys are stored at both devices. In some embodiments, at least one device (e.g., a reader device) stores the initialization key(s) (e.g., a symmetric key, an asymmetric key pair) in local memory as part of performance of a manufacturing process for the device. The second device (e.g., a thin client device) may receive the initialization key(s) from an acceptance cloud (e.g., a server computer configured to perform terminal processing). The initialization key(s) are utilized to perform a secure exchange of the devices' respective public keys. Once these public keys are exchanged, the devices may proceed to establishing a secure connection with which subsequent operations may be performed.
Systems and methods disclosed herein include a mobile solution to enable users to perform financial transaction over a network using a mobile device. These techniques allow users to maintain a single personal account identifier or number (“PAN”) on the user's mobile device and to utilize it to access a plurality of linked financial accounts and sub-accounts. Any one of the accounts can be selected by a user on the mobile device to remotely deposit funds to that account based on an image of a financial payment instrument. The image can be obtained using image capture technology on the user's mobile device. Users can perform a financial transaction using the verified images over a network in order to conduct a remote financial transaction such as applying a deposit, a payment, or cash load to a designated account which is linked to the user's mobile account in real-time or near real-time.
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
Methods, systems, and computer program products for time series analysis using a time interval embedding based attention mechanism are provided. An example method may include receiving training data associated with a time series of a plurality of events, determining a plurality of time intervals between each pair of events of the plurality of events of the time series, generating a time interval embedding for each time interval of the plurality of time intervals to provide a plurality of time interval embeddings, calculating a plurality of attention weights for an attention mechanism of a machine learning model based on the plurality of time interval embeddings, and generating a trained machine learning model based on the attention weights for the attention mechanism of the machine learning model.
System, Method, and Computer Program Product for Predicting Consumer Behavior Based on Demographics and New Product Features Using Machine Learning Models
Systems, methods, and computer program products are provided for predicting consumer behavior based on demographics and new product features using machine learning models. An example method includes receiving spending behavior data, payment device feature data, and transaction data associated with existing payment devices and proposed spending behavior data and proposed payment device feature data associated with a proposed payment device. A machine learning model (MLM) is trained to predict a transaction metric associated with the transaction data based on the spending behavior data and the payment device feature data for the existing payment devices. The trained MLM predicts a predicted transaction metric based on the proposed spending behavior data and the proposed payment device feature data associated with the proposed payment device. A communication is transmitted based on the predicted transaction metric.
Methods and systems for quantifying interactions between data objects in databases based on bipartite graph analysis are disclosed, particularly related to the identification, counting, and enumeration of 2×2-bicliques, also referred to as “butterflies.” A computer system (which can comprise, e.g., a distributed computing system comprising multiple distributed computing nodes) can enumerate through pairs of vertices that are common neighbors to other vertices in a bipartite graph. Based on these pairs of neighbor vertices, the computer system can count 2×2-bicliques, including counting the total number of 2×2-bicliques, the number of 2×2-bicliques per vertex in the bipartite graph, and the number of 2×2-bicliques per edge in the bipartite graph. Additionally, methods according to embodiments can be used to enumerate and list all 2×2-bicliques in a bipartite graph.
Methods, systems, and computer program products for providing global personalized recommendations are provided. An example method may include generating embeddings for a first plurality of entities based on a first dataset, determining first identifiers of the first plurality of entities included in the first dataset that corresponds to second identifiers of a second plurality of entities included in a second dataset to provide a matched set of entities, wherein the second dataset includes attribute data associated with each entity of the second plurality of entities, generating a graph representation of the second plurality of entities, and wherein the graph includes nodes and each node represents an entity of the second plurality of entities, determining one or more first nodes that lacks data associated with a node embedding, and generating data associated with the node embedding for the one or more first nodes using a graph neural network (GNN) machine learning model.
Systems, methods, and computer program products are provided for on-vehicle electronic fee collection. An example system includes at least one processor configured to receive event data from a vehicle operated by a user, the event data including a digital signature based on sensor data generated by at least one sensor of the vehicle. The at least one processor may be configured to determine a merchant system from a plurality of merchant systems based on the payment event and determine a payment event based on the event data. The at least one processor may be configured to generate transaction data based on the payment event and the merchant system and transmit a payment request message including the transaction data to the vehicle. The at least one processor may be configured to process a payment transaction based on the transaction data in response to receiving a payment confirmation message from the vehicle.
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
35.
Method, System, and Computer Program Product for Ensemble Learning With Rejection
Methods, systems, and computer program products are provided for ensemble learning. An example system includes at least one processor configured to: (i) generate a rejection region for each baseline model of a set of baseline models (ii) generate a global rejection region based on the rejection regions of each baseline model; (iii) train an ensemble machine learning model; (iv) update, based on a baseline model predictive performance metric for each baseline machine learning model, the set of baseline machine learning models; and (iv) repeat (i)-(iv) until there is a single baseline model in the set of baseline models or a predictive performance or global acceptance ratio of the ensemble model satisfies a threshold.
Methods and systems for inducing model shift in a malicious computer's machine learning model is disclosed. A data processor can determine that a malicious computer uses a machine learning model with a boundary function to determine outcomes. The data processor can then generate transition data intended to shift the boundary function and then provide the transition data to the malicious computer. The data processor can repeat generating and providing the transition data, thereby causing the boundary function to shift over time.
Techniques are disclosed for performing authenticated communication. The techniques include using a public matrix A, a public matrix B, and a vector x that is a private signing key. An MPC in the head protocol may be performed by a prover device. A prover device may communicate with a verifier device to prove that the prover device is in possession of the private key that was used to sign a message that was received by the verifier device.
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 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
38.
METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR INTEGRATING A FINITE STATE MACHINE (FSM) IN A CHATBOT SYSTEM
Methods, systems, and computer program products are provided for integrating a finite state machine (FSM) in a chatbot system. An example method includes: storing an FSM graph including states connected in a directed graph; receiving a message including text from a user device; automatically determining that the text is associated with the dialog flow type; in response to determining that the text is associated with the dialog flow type, retrieving the FSM graph and the function configured to be applied during each of the states of the FSM graph; inputting the text, the FSM graph, and the function into an LLM, causing the LLM to generate a response to the text; receiving the response from the LLM; and outputting the response to the user device.
G06F 40/35 - Représentation du discours ou du dialogue
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
G06F 9/448 - Paradigmes d’exécution, p. ex. implémentation de paradigmes de programmation
Transactions between account-based endpoints are performed in a two-step process that first qualifies the recipient's validity and then performs the actionable transfer. The qualification step, unlike a payment pre-qualification, validates the recipient account validity while collecting information required for filling out a transaction data set. The information may include anti-money laundering and know-your-customer information as well as specific account details needed for on-boarding. A recipient payouts service provider may be assigned a tokenized bank identification number for use in routing the transfer through existing financial processing networks. Data constructs, minimum required information, and format checks may be facilitated by initiator-side and recipient-side application program interfaces.
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 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
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 method is disclosed. The method includes receiving claim requests from a plurality of service provider computers associated with a plurality of service providers for fulfillment by a plurality of payors. Each claim request includes service provider information, payor information, and beneficiary information. The method also includes validating the claim requests, and determining for each service provider of the plurality of service providers, a net amount to be transferred to the service provider. The net amount is associated with a plurality of claim requests made by the service provider for different beneficiaries serviced by the service provider. The different beneficiaries may be associated with different payors. The method further includes facilitating for each of the service providers, a single funds transfer in the net amount to be transferred to the service provider.
43 - Services de restauration (alimentation); hébergement temporaire
Produits et services
Providing access to curated dining experiences; organizing and hosting exclusive culinary events; offering payment cardholder-based access to premium dining events and restaurant openings; providing information related to restaurants and dining events
A method is disclosed. The method includes determining, by a delegated certificate authority computer, a tier from a plurality of tiers for a digital wallet provider based on a list of qualifying criteria. The method also includes generating a digital certificate based on the tier, where the digital certificate is used by a digital wallet application computer associated with the digital wallet provider to complete interactions using a digital currency maintained by a blockchain network. The method further includes transmitting, by the delegated certificate authority computer to a digital wallet application computer, the digital certificate.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
43.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR DYNAMICALLY CONFIGURING INSTALLMENT-BASED TRANSACTIONS DURING AUTHENTICATION PROCESSING
Systems, methods, and computer program products are provided for dynamically configuring installment-based transactions during processing. The system includes a processor configured to receive a first authentication request from a merchant system, the first authentication request associated with a transaction between a user and the merchant. The processor is also configured to determine eligibility for installment payment based on the first authentication request and generate a unique uniform resource locator (URL) associated with an installment selection interface. The unique URL is configured to permit access to the installment selection interface. The processor is further configured to transmit the unique URL to the merchant system and receive a user selection of an installment plan via the installment selection interface. The processor is further configured to generate a second authentication request and cause an issuer system to initiate an installment-based transaction, by transmitting the second authentication request to the issuer system.
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
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
44.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR INITIATING PULL PAYMENTS
Systems, methods, and computer program products are provided for initiating pull payments. The system includes a processor configured to receive a transaction request from a mobile device, the transaction request initiated by the mobile device scanning encoded indicia. The processor is also configured to communicate an authentication request to an authentication system, the authentication request configured to cause the authentication system to prompt the user for a proof of identity. The processor is further configured to receive the proof of identity from the mobile device. The processor is further configured to, in response to receiving the proof of identity, identify a payment enabler system based on the transaction request. The processor is further configured to initiate a pull payment transaction, via payment enabler system, to transfer the transaction value from an account associated with the account identifier to a merchant account associated with the merchant identifier.
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
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06K 19/06 - Supports d'enregistrement pour utilisation avec des machines et avec au moins une partie prévue pour supporter des marques numériques caractérisés par le genre de marque numérique, p. ex. forme, nature, code
A server computer can receive, from a resource provider computer operated by a resource provider, an authorization request message comprising a flexible credential and an amount for a transaction conducted between a user and the resource provider. The flexible credential can be associated with multiple sources. The server computer can then determine a subset of user rules of a set of user rules associated with the flexible credential to apply to the transaction. The server computer can determine a subset of resource provider rules of the resource provider based on the subset of user rules to apply to the transaction. The server computer can then apply the subset of user rules and the subset of resource provider rules to the transaction.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
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
46.
Method, System, and Computer Program Product for Dynamic Data Allocation to Nodes in Distributed Systems
Methods, systems, and computer program products are provided for dynamic data allocation to nodes in distributed systems. The method may include storing data blocks at nodes; receiving, from the nodes, node health data associated with the nodes; and for a data block, performing a dynamic data allocation including: receiving, from a node on which that data block was stored, age data associated with an age of that data block; receiving, from each client that accessed that data block at the node, network latency data associated with a network latency of that client for accessing that data block; generating, based on (i) the node health data, (ii) the age data, and (iii) the network latency data, a node assignment for that data block; and in response to determining that the node assignment is different than a current node, moving that data block from the current node to the node assignment.
A method is disclosed. The method includes receiving, from a storage application server, a data packet comprising access data. The method also includes receiving, from a transport computer, a request for the data packet, after the transport computer receives a message comprising a value and a resource provider identifier from a resource provider computer. The method further includes transmitting, to the transport computer, a response comprising the data packet. The transport computer is programmed to receive the data packet, generate an authorization request message comprising the access data, the resource provider identifier, and the value, and transmit the authorization request message to an external computer for authorization processing.
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 20/42 - Confirmation, p. ex. contrôle ou autorisation de paiement par le débiteur légal
A method of testing a software application on a first user device is disclosed. The method includes determining that a transceiver application on the first user device is unable to communicate with a first near field communication (NFC) application programming interface (API) associated with a first NFC hardware in the first user device. The method also includes forming a data connection between the first user device and a second user device with a second NFC API associated with a second NFC hardware in the second user device, and conducting one or more interactions between the software application and an access device via the second user device and the second NFC API associated with the second NFC hardware. The second user device communicates with the access device via NFC.
H04B 5/40 - Systèmes de transmission en champ proche, p. ex. systèmes à transmission capacitive ou inductive caractérisés par des composants spécialement adaptés à la transmission en champ proche
H04B 5/72 - Systèmes de transmission en champ proche, p. ex. systèmes à transmission capacitive ou inductive spécialement adaptés à des fins spécifiques pour la communication locale à l'intérieur d’un dispositif
49.
METHOD AND SYSTEM FOR KEY RECOVERY USING GROUP STRUCTURE
A method includes a user device generating a key recovery message comprising a public key or an identifier thereof associated with an account. The public key corresponding to a first private key associated with the user device. The user device can provide the key recovery message to a smart contract on a blockchain. The user device can receive a recovery detected message from a server computer that monitors the smart contract. After providing the key recovery message to the smart contract, the user device can generate a new private key to replace the first private key.
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
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
50.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR ANALYZING LARGE LANGUAGE MODELS
Systems, methods, and computer program products are provided for analyzing large language models. An example system includes at least one processor configured to generate a plurality of model queries based on a semantic input, each model query of the plurality of model queries includes the semantic input and a different non-semantic input, input the semantic input into a language model, resulting in a first model output, perturb the language model with the plurality of model queries, resulting in a plurality of perturbed model outputs, determine a model harmonic value for the language model based on an angle between the first model output and the plurality of perturbed model outputs, and retrain or select the language model based on the model harmonic value satisfying at least one threshold.
Provided is a computer-implemented method for implementing a blockchain-based rewards network. The method includes establishing a blockchain network including administrative nodes, client nodes, and entity nodes, maintaining a distributed ledger on at least a portion of the administrative nodes of the blockchain network, receiving, from a plurality of entities, rewards data including a plurality of offers, each offer of the plurality of offers corresponding to at least one entity identifier, publishing the rewards data to the distributed ledger, querying the distributed ledger based on at least one entity identifier received from a client node, and determining, based on the distributed ledger, at least one offer corresponding to the at least one entity identifier received from the client node.
A method includes a computer receiving a request to conduct an interaction from a mobile device. The computer obtains a computer address and provides the computer address to the mobile device. The mobile device provides an access request to the computer address, and the access request is thereafter routed to an identity provider computer. The identity provider computer identifies identity data associated with the mobile device or a user of the mobile device. The computer obtains the identity data or a derivative of the identity data from the identity provider computer. The computer determines if the identity data or the derivative of the identity data matches previously stored identity data or a previously stored derivative of identity data. If a match is determined, the computer provides a list of user device identifiers to the mobile device.
Provided is a method for aggregating data from real-time events (e.g., payment transactions). The method may include receiving event (e.g., transaction) data associated with a plurality of events (e.g., payment transactions). First aggregation of interest data associated with a type of aggregation of interest may be received. A first key associated with each event (e.g., transaction) may be determined based on a first portion of the event (e.g., transaction) data associated with each event (e.g., transaction) and the first aggregation of interest data. A first value based at least partially on a first plurality of the first keys associated with a first subset of the plurality of payment transactions may be communicated based on a first user request. A system and computer program product are also disclosed.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06F 7/08 - Tri, c.-à-d. rangement des supports d'enregistrement dans un ordre de succession numérique ou autre, selon la classification d'au moins certaines informations portées sur les supports
G06Q 20/32 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des dispositifs sans fil
54.
System, Method, and Computer Program Product for Consent Management
A system, method, and computer program product are provided for consent management. A method may include receiving a first data request for user data associated with a user, the user data stored in a user data database; communicating a consent request to the requester system; receiving a consent response from the requester system; storing consent data associated with the consent response for the user data requested in the first data request in an immutable ledger; receiving a consent verification request from the user data database, the consent verification request based on a second data request for the user data from the requester system to the user data database; verifying the consent verification request based on the consent data; and communicating a consent verification response to the user data database, the consent verification response indicating consent from the user to share the user data with the requester system.
A method is disclosed. The method includes storing data relating portioning plans and credentials that can be used with the portioning plans. The method also includes receiving from a resource provider computer, an eligibility check message comprising an initial credential, determining that the initial credential is one of the stored credentials, and providing to the resource provider computer, one or more portioning plans associated with the initial credential; receiving a selection of a portioning plan of the one or more portioning plans. The method also includes receiving an authorization request message including the initial credential and a value, substituting a substitute credential for the initial credential in a credential data field in the authorization request message and placing the initial credential in a supplemental data field to form a modified authorization request message, and transmitting the modified authorization request message to an authorizing entity computer.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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 20/40 - 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 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
A computer obtains interaction data and aggregated data for a current interaction. The current interaction relates to a device requesting access to a resource. The computer generates a feature vector using the interaction data and the aggregated data and generates a prompt comprising a set of feature-label pairs. Each feature-label pair comprises a task-specific label and an additional feature vector including additional interaction data and additional aggregated data. The additional interaction data and the additional aggregated data are related to an additional interaction of a same type of classification as the current interaction. The computer loads a pre-trained machine learning model trained to determine predictions for specific tasks. The computer inputs the prompt and a query including the feature vector into the pre-trained machine learning model. The computer determines a task-specific prediction for the query and the prompt, the task-specific prediction specifying a response state to the current interaction.
Employment recruiting services; personnel recruitment services; providing career and employment information via social media websites and mobile applications; providing online employment information in the field of employment, recruitment, careers, job resources, and job listings; recruitment advertising services, namely, posting job notices for the purpose of recruiting potential employees
Ethical data tracker systems and methods are disclosed. A payment network computer receives a token request from an application running on a client device. The token request includes user contact information and a merchant identifier. A token server computer generates a token associated with the merchant identifier. The payment network computer maps the token to the user contact information and the merchant identifier, stores the token, the user contact information, and the merchant identifier in a database, and determines a validation of a mapping in the database of a token and a merchant identifier received from a network service provider. The payment network computer authorizes or prohibits the network service provider to communicate with the account holder via the user contact information based on the determining of the validation of the mapping in the database of the token and the merchant identifier received from the network service provider.
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 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
60.
MANAGING ATTACK SURFACE VULNERABILITIES OF A NETWORK
Embodiments include creating a simplified network tree from information contained in network devices, including load balancers and firewalls, for security analysis. The tree may model relevant security devices or network configuration points in the network to simplify the study of a network for compliance and network anomalies. A list of network devices, including externally exposed devices with externally exposed IP addresses and a plurality of internal network devices may be stored. A graph may be generated which may include a plurality of network tree paths, each network tree path containing nodes representing IP addresses of network devices in the network tree path and links between nodes representing a configuration policy. The graph may be used to detect network vulnerabilities.
H04L 43/045 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux pour la visualisation graphique des données de surveillance
36 - Services financiers, assurances et affaires immobilières
Produits et services
Financial services; monetary services; banking services; credit card services; debit card services; charge card services; pre-paid card services; provision of prepaid cards and tokens; smart payment card services; electronic credit and debit transactions; electronic funds transfer; payment processing services; transaction authentication and verification services; check verification services; cash replacement rendered by credit cards and debit cards; currency exchange services; online banking services; bill payment services; deposit access and automated teller machine services; check cashing and cash disbursement services; dissemination of financial information and electronic payment data including via a global computer network; processing of financial transactions online via computer or telecommunication networks or via telecommunication, mobile or wireless devices; financial services, namely providing a digital currency wallet.
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
(1) Business information services, namely, providing information regarding business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing; business advisory services, namely, providing advise regarding business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing; business analysis services, namely, providing insights to businesses in the fields of business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing; marketing services for businesses; advertising services for businesses
(2) Financial services, namely, banking services; pre-paid card services, namely, authorization services, verification services, payment processing services, transaction processing services in the field of consumer payments, payment transaction settlement services; electronic credit and debit card transaction processing, electronic funds transfer, smart cards and electronic cash services, namely, authorization services, verification services, payment processing services in the field of credit card and debit card payments, credit card and debit card transaction processing services, payment transaction settlement services; electronic funds disbursement services, cash disbursement, cash replacement rendered by credit cards and debit cards, electronic cash transactions processing, check cashing, deposit access and automated teller machine (ATM) banking services, payment processing services namely, authorization services, verification services, transaction processing services, transaction settlement services, remittances, money transfer services in the nature of web-based money transfers provided by means of a global computer network; processing of financial transactions online via a global computer network or via telecommunication, mobile or wireless devices, payment transaction authentication and verification services; electronic funds transfer and currency exchange services; dissemination of financial information and electronic payment data via a global computer network or via telecommunication, mobile or wireless devices; Financial information services, namely, providing business with information regarding payment services and business credit and debit cards; financial advisory services; financial analysis services; financial consulting services; financial management services; financial planning services; financial research services
(3) Providing a website featuring educational resources and information in the fields of business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing educational services, namely, providing online classes, seminars, workshops, presentations, webinars, and conferences in the fields of business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing a website featuring educational resources and information in the fields of business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing educational services, namely, providing online classes, seminars, workshops, presentations, webinars, and conferences in the fields of business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing
36 - Services financiers, assurances et affaires immobilières
Produits et services
Financial services, namely, banking services; pre-paid card services, namely, authorization services, verification services, payment processing services, transaction processing services in the field of consumer payments, payment transaction settlement services; electronic credit and debit card transaction processing, electronic funds transfer, smart cards and electronic cash services, namely, authorization services, verification services, payment processing services in the field of credit card and debit card payments, credit card and debit card transaction processing services, payment transaction settlement services; electronic funds disbursement services, cash disbursement, cash replacement rendered by credit cards and debit cards, electronic cash transactions processing, check cashing, deposit access and automated teller machine (ATM) banking services, payment processing services namely, authorization services, verification services, transaction processing services, transaction settlement services, remittances, money transfer services in the nature of web-based money transfers provided by means of a global computer network; processing of financial transactions online via a global computer network or via telecommunication, mobile or wireless devices, payment transaction authentication and verification services; electronic funds transfer and currency exchange services; dissemination of financial information and electronic payment data via a global computer network or via telecommunication, mobile or wireless devices; Financial information services, namely, providing business with information regarding payment services and business credit and debit cards; financial advisory services; financial analysis services; financial consulting services; financial management services; financial planning services; financial research services.
Business information services, namely, providing information regarding business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing; business advisory services, namely, providing advise regarding business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing; business analysis services, namely, providing insights to businesses in the fields of business funding, business growth, business grants, fraud protection, disaster support for business, business credit and debit cards, offers and rewards for businesses, business optimization, cash flow management, integrated bookkeeping, streamlining business operations, and business marketing; marketing services for businesses; advertising services for businesses
69.
GLOBAL RELYING PARTY SYSTEM FOR VALIDATING DIGITAL IDENTITY CREDENTIALS
Techniques described herein enable a digital certificate (e.g., a mobile Driver's License (mDL)) to be used as a proxy for a credential. Using the digital certificate as a proxy for the credential can improve transaction security and benefit from trust established by processes implemented by a certification authority. The techniques can add functionality to a digital certificate since the digital certificate can be used as an account credential in addition to its previous function.
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
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
70.
SECURE DATA EXCHANGE MATCHING ACROSS IDENTITY PROVIDERS
A method includes receiving a first encrypted first identity attribute. A first doubly encrypted first identity attribute is formed by encrypting the first encrypted first identity attribute. A second doubly encrypted first identity attribute is formed by encrypting the first encrypted first identity attribute. They are transmitted to a user device, which removes a user layer of encryption on each to form a second encrypted first identity attribute and a third encrypted first identity attribute. Layers of encryption are added to the second encrypted first identity attribute to form a third doubly encrypted first identity attribute and the third encrypted first identity attribute to form a fourth doubly encrypted first identity attribute. The server computer receives them and transmits, to the second identity provider computer, the fourth doubly encrypted first identity attribute. The second identity provider computer obtains a first identity attribute and compares it to a second identity attribute.
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 9/14 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité utilisant plusieurs clés ou algorithmes
71.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR STATE CORRECTION OF ARTIFICIAL INTELLIGENCE MODELS
Systems, methods, and computer program products are provided for state correction of stateful machine learning (ML) models. A system may include a processor configured to receive an input for stateful ML model, generate an output of the stateful ML model based on the input, determine whether the output of the stateful ML model corresponds to a ground truth value associated with the input, assign an initial state of the stateful ML model as an active state of the stateful ML model based on determining that the output of the stateful ML model corresponds to the ground truth value associated with the input, and assign a correction state of the stateful ML model as the active state of the stateful ML model based on determining that the output of the stateful ML model does not correspond to the ground truth value associated with the input.
A method is disclosed. The method includes receiving interaction data related to a plurality of interactions in a time period, determining a multiple variable regression formula, and then determining a coefficient of determination associated with the multiple variable regression formula and the interaction data. The method further includes determining if the coefficient of determination satisfies a threshold or is maximized. If the coefficient of determination does not satisfy the threshold or is not maximized, then adjusting the slope coefficients. If the coefficient of determination does satisfy the threshold or is maximized, then using the multiple variable regression formula to determine risk associated with future interactions.
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
73.
SECURE REMOTE TOKEN RELEASE WITH ONLINE AUTHENTICATION
A system and techniques are described herein for providing authentication. The technique includes registering user authentication data such as biometrics data with a communication device. The authentication data is linked to an account or service provider, and is used to verify the identity of the user when accessing the account. The communication device may obtain a public/private key pair, for which the pubic key may be stored on a secure remote server. When the user attempts to access the account or service provider, the user may provide the authentication data to authenticate the user to the communication device. Thereafter, the communication device may sign an authentication indicator using the private key and send the authentication indicator to the secure remote server. Upon verification of the signature using the public key, the secure remote server may grant access to the user, for example, by releasing a token.
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
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
74.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR GENERATING IMPROVED EMBEDDINGS FOR MACHINE LEARNING BASED ON TOKEN TYPE
Systems, methods, and computer program products are provided for generating improved embeddings for machine learning based on token type. The system includes a processor configured to receive and separate text data associated with a string of text into mathematical tokens of a mathematical token type and remaining tokens of a remaining token type. The processor may be configured to input the mathematical tokens into a first machine learning model (MLM) associated with the mathematical token type to generate first embeddings comprising a respective first embedding for each respective mathematical token. The processor may be configured to input the remaining tokens into a second MLM associated with the remaining token type to generate second embeddings comprising a respective second embedding for each respective remaining token of the remaining token type. The processor may be configured to input the first and second embeddings into a third MLM to perform a task.
In some embodiments, a computer-implemented method, includes receiving, at a fleet-based merchant discount portal of a payment processing network, an advice message from an acquirer, the advice message being associated with a fleet-based vehicle energy purchase initiated at an access device of a merchant; performing a fleet-based merchant discount qualification assessment of the advice message at the fleet-based merchant discount portal to determine whether to apply a fleet-based merchant discount to the fleet-based vehicle energy purchase; and when the fleet-based merchant discount qualification assessment yields that the fleet-based merchant discount is warranted, utilizing a fleet-based merchant discount advice message to perform the fleet-based merchant discount of the fleet-based vehicle energy purchase, the fleet-based merchant discount advice message being created by adding fleet-based merchant discount fields to the advice message to discount the fleet-based vehicle energy purchase.
An issuing authority (IA) may validate the identity of a user and issue a digital license to the user. IA may generate IA public-private key pair, and provide IA public key to the certification authority (CA). IA may sign the digital license with IA private key, and provision the signed digital license on the user device. IA may request CA to certify the digital license. CA may use IA public key to validate the digital license, and sign IA public key with CA private key, thereby generating a digital certificate associated with the issuing authority that is linked to the digital license. A relying party may use CA public key to validate the digital license. The relying party can retrieve the information from the digital license and trust that the retrieved information is legitimate.
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 21/10 - Protection de programmes ou contenus distribués, p. ex. vente ou concession de licence de matériel soumis à droit de reproduction
G06F 21/33 - Authentification de l’utilisateur par certificats
77.
SECURE AND PRIVACY PRESERVING MESSAGE ROUTING SYSTEM
A method is disclosed. The method includes receiving, by a user device from the access device, a routing path list comprising a first set of network nodes. After receiving the routing path list, the user device determines a routing options list comprising a second set of network nodes based on the first set of network nodes in the routing path list. The method also includes obtaining an encrypted credential or token, and transmitting, by the user device to the access device, the routing options list, and the encrypted credential or token to the access device. The access device transmits an authorization request message comprising the encrypted credential or token, and the routing options list to a server computer via at least some of the network nodes in the second set of network nodes. The server computer may be an authorizing entity computer.
Provided are systems for generating a machine learning model for classification tasks using unadversarial training that include a processor to perform an unadversarial training procedure to train a machine learning model to provide a trained machine learning model. When performing the unadversarial training procedure, the processor is programmed or configured to receive a training dataset including a plurality of training samples; generate a noise vector for the plurality of training samples based on a uniform distribution; perturb each training sample of the plurality of training samples; obtain a gradient; generate an updated noise vector based on the gradient; perturb each training sample of the plurality of training samples based on the updated noise vector; and update a model weight of the machine learning model based on the second plurality of perturbed training samples to provide the trained machine learning model. Methods and computer program products are also provided.
Systems, methods, and computer program products are provided for generating and improving multitask learning models. An example method includes determining a first accuracy metric based on at least two machine learning models performing a plurality of tasks, receiving a multitask learning model including at least one shared layer and a plurality of task-specific layers, determining a second accuracy metric based on the multitask learning model having a first number of shared layers, determining a third accuracy metric based on the multitask learning model having a second number of shared layers, comparing the accuracy metrics, repeating until at least one termination condition is satisfied, and determining a target number of shared layers for the multitask learning model based on at least one of the second accuracy metric, the third accuracy metric, the first number of shared layers, the second number of shared layers, or any combination thereof.
Systems, methods, and computer program products are provided for improved machine learning models for generating tabular data. An example system includes at least one processor configured to receive tabular data associated with at least one data record including values associated with features. Each feature has a feature type. Mask data associated with masking at least one value is received. A stochastic latent space embedding for each data record is generated based on the tabular data and the mask data using at least one encoder machine learning model. At least one generated data record is generated based on the stochastic latent space embedding and the feature type using at least one decoder machine learning model including a plurality of output distributions. Each generated value of the plurality of each generated data record is generated by one of the output distributions based on the feature type.
Systems, methods, and computer program products are provided for quantifying contributions of prior inputs in sequence-based machine learning models. The system includes at least one processor configured to: obtain input data associated with a sequence of inputs to be processed by a machine learning model to generate a model output associated with a current input; learn, based on the input data, using a time decay attribution model, a time decay factor; generate, based on the time decay factor, a temporal contribution of the inputs; generate, based on how machine learning model inference results change independently for the inputs, individual contributions of the inputs; and combine the temporal contributions and the individual contributions of the inputs to determine combined contributions of the inputs prior to the current input to the model output associated with the current input.
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
82.
Method, System, and Computer Program Product for Processing Transactions Using Electronic Wallets
A computer-implemented method includes: storing, by a payment application, payment device data including: first and second payment device identifiers and first and second wallet identifiers corresponding to first and second electronic wallets in which first and second payment device credentials of first and second payment devices are respectively stored; initiating a payment transaction with a merchant system; displaying the first and second payment device identifiers; receiving a user input from the user of the user device, the user input comprising a selection of the first payment device identifier; determining that the first electronic wallet includes the first payment device credentials of the first payment device; and facilitating a transfer of payment data between the merchant system and the first electronic wallet to initiate processing of the payment transaction.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/12 - Architectures de paiement spécialement adaptées aux systèmes de commerce électronique
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
Techniques include receiving an authorization request message for an interaction by a processor server computer, the authorization request message comprising interaction data comprising an interaction amount, and transmitting the authorization request message to an authorization computer. The processor server computer receives an authorization response message from the authorization computer indicating that the interaction is approved. Based on the interaction data, an indicator, indicating a likelihood that the interaction amount in the authorization request message will equal a clearing amount for the interaction, is generated along with a modified authorization response message comprising the indicator. The processor server computer transmits, to the resource provider computer, the modified authorization response message. The processor server computer generates a clearing message based on the indicator and at least a subset of the interaction data and transmits the clearing message, thereby causing clearing and settlement of the interaction.
Methods and systems for generating embeddings using a multi-scale machine learning model (also referred to as an "encoder model") and performing various processes (e.g., classification) based on those embeddings are disclosed. Additionally disclosed are contrastive learning methods that can be used to train machine learning models according to embodiments. A data sequence can be separated into one or more sets of data subsequences based on window lengths (e.g., "long", "medium", and "short" window lengths). The machine learning model, comprising a sequence module and one or more window modules, can process the data sequence and the one or more sets of data subsequence to generate a set of partial sequence embeddings and one or more sets of partial window embeddings (which can be generated, in part, using the set of partial sequence embeddings). The one or more sets of window embeddings can be combined to produce an output embedding.
A server computer that implements an efficient sampling technique for imbalanced transactions. Transaction data comprising unlabeled transaction data and fraudulent transaction data is encoded to form (i) a first set of encoded data associated with fraudulent transactions and unlabeled transactions that are similar to fraudulent transactions, and (ii) a second set of encoded data associated with unlabeled transactions. A first sampling process is executed with respect to the first set of encoded data to obtain a first sampled set of encoded data, and a second sampling process is executed with respect to the second set of encoded data to obtain a second sampled set of encoded data. An optimal sampling size of the transaction data is determined based on whether a performance of a machine learning model that classifies the first sampled set of encoded data and the second sampled set of encoded data satisfies a condition.
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
An application or device is authenticated using secure application data validation. A server computer receives an authentication request comprising an application identifier or a user device identifier associated with a user device, the authentication request originating from the user device. The server computer receives a set of behavioral data associated with the application or the user device. Responsive to receiving the application identifier or device identifier, the server computer obtains a fuzzy vault associated with the application identifier or the user device identifier. The server computer determines a reconstructed key value using the fuzzy vault and the set of behavioral data. The application or the user device is authenticated using the reconstructed key value.
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
A method and system for leveraging an existing issuer user application, associated with a payment network, to create centralized merchant loyalty platform. The centralized merchant loyalty platform consolidates computing resources from different merchant systems to a centralized processing system. The centralized processing system creates a scalable computing platform that allows for loyalty programs associated with a plurality of different merchants to be seamlessly accessed through the existing issuer user application.
G06Q 30/0226 - Systèmes d’incitation à un usage fréquent, p. ex. programmes de miles pour voyageurs fréquents ou systèmes de points
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
88.
SEMI-SUPERVISED SYSTEM FOR DOMAIN SPECIFIC SENTIMENT LEARNING
Automated computer systems and methods to determine a sentiment of information in digital information or content are disclosed. One aspect includes deriving, by a processor, the digital information from a source; generating, by the processor, a domain-specific machine learning sentiment score, based on the digital information, by one model of at least two machine learning models; autonomously mapping, by the processor, a non-domain specific knowledge graph of associations between elements in a set of digital contextual information; receiving, by the processor, sentiment graphs, each sentiment graph defining a sentiment; generating, by the processor, a graph sentiment score based on the non-domain specific knowledge graph and the sentiment graphs; generating, by the processor, a final sentiment score based on the graph sentiment score and the domain-specific machine learning sentiment score; and determining the sentiment of the information in the digital information or content via the final sentiment score.
Methods, systems, and computer program products for universal depth graph neural networks may obtain a graph G including an adjacency matrix A and an attribute matrix X and train a graph convolutional network using according to the following updating Equation: H=σ(ŜdXW), where H is an output embedding matrix, σ(·) is a nonlinear activation function, S is a filter, X is an attribute matrix, W is a trainable weight matrix, and d is a trainable depth parameter.
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
90.
Method, System, and Computer Program Product for Normalizing Embeddings for Cross-Embedding Alignment
Provided is a method for normalizing embeddings for cross-embedding alignment. The method may include applying mean centering to the at least one embedding set, applying spectral normalization to the at least one embedding set, and/or applying length normalization to the at least one embedding set. Spectral normalization may include decomposing the at least one embedding set, determining an average singular value of the at least one embedding set, determining a respective substitute singular value for each respective singular value of a diagonal matrix, and/or replacing the at least one embedding set with a product of the at least one embedding set, a right singular vector, and an inverse of the substitute diagonal matrix. The mean centering, spectral normalization, and/or length normalization may be iteratively repeated for a configurable number of iterations. A system and computer program product are also disclosed.
G06F 5/01 - Procédés ou dispositions pour la conversion de données, sans modification de l'ordre ou du contenu des données maniées pour le décalage, p. ex. la justification, le changement d'échelle, la normalisation
A method includes a server computer receiving, from a first data provider computer, encrypted data derived from first identity data and a cryptographic key or derivative thereof stored at the first data provider computer. The server computer transmits, to a second data provider computer, the encrypted data and/or the cryptographic key or derivative thereof. The server computer receives, from the second data provider computer, intermediate data derived from second identity data stored at the second data provider computer. The server computer determines if the first identity data and the second identity data are duplicates while the first identity data and the second identity data are encrypted. The server computer removes one of encrypted first identity data, derived from the first identity data, and encrypted second identity data, derived from the second identity data, from a memory in the server computer.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
H04L 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
92.
SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR INTERFACING WITH A PLURALITY OF MACHINE-LEARNING MODELS
Systems, methods, and computer program products are provided for interfacing with machine-learning models. The system includes at least one processor configured to: receive, from a plurality of remote issuer systems via an interface with the at least one processor, a plurality of model outputs from a plurality of machine-learning models, each model output of the plurality of model outputs resulting from a same input processed by a separate machine-learning model trained by an issuer system of the plurality of remote issuer systems; and aggregate the plurality of model outputs to generate an aggregated output.
A transaction-processor tester system for examining a transaction processor is disclosed. The system includes a rule generator, a storage medium, a rule selector, a transaction generator, a payload parser, and a payload validator. The storage medium is to receive and store random transaction rules. The rule selector is to receive an input indicative of at least one selected rule type, and retrieve a subset of the random transaction rules. The transaction generator is to generate simulated transactions based on predefined transaction map and transaction-parameter conditions, check the simulated transactions against the subset of rules, and output expected values based on the simulated transactions that are in accordance with the subset of rules. The payload includes an output of the transaction processor from processing the subset of the simulated transactions. The output of the transaction processor includes actual values associated with processing the subset of the simulated transactions.
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.
Method, System, and Computer Program Product for Providing a Type Aware Transformer for Sequential Datasets
Provided are methods that include receiving interaction data associated with a plurality of interactions, the interaction data including interaction records that include a plurality of fields including a static field and a dynamic field, generating a static interaction embedding representation based on static field data associated with the static field and a first transformer model, generating a plurality of dynamic interaction embedding representations based on dynamic field data associated with the dynamic field of a sequence of interaction records and a second transformer model, generating a first intermediate input and a plurality of second intermediate inputs, generating a static sequence embedding representation and dynamic sequence embedding representations based on a third transformer model, and generating at least one prediction based on inputting the static sequence embedding representation and the plurality of dynamic sequence embedding representations to a machine learning model. Systems and computer program products are also disclosed.
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
A method includes a first user device generating an interaction message during an interaction between the first user device and a second user device. The interaction message includes an amount, an expiry time, and a condition. The first user device can provide the interaction message to the second user device. The second user device can obtain a witness that satisfies the condition. The first user device can receive the witness or a proof. The first user device can verify that the witness satisfies the condition or the validity of the proof. A transfer of the amount from a first user to a second user according to the interaction is facilitated using a blockchain.
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 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
A method and system for migrating a payment instrument portfolio. A payment network computer receives a payment instrument portfolio conversion request message from an issuer computer to convert a payment instrument portfolio from a prior payment instrument scheme to a new payment instrument portfolio based on a new payment instrument scheme. The request message includes information about existing payment instrument references from the prior payment instrument scheme. The payment network computer creates enrollments based on the information about the existing payment instrument references and sends a portfolio migration event notification message to a payment instrument requestor partner computer associated with a payment network payment instrument requestor identifier subscribed to a new event type for the payment instrument portfolio migration. The payment network computer receives a provision payment instrument from the payment instrument requestor partner computer and sends a new payment instrument provisioning approval request message to the issuer computer.
G06Q 40/06 - Gestion de biensPlanification ou analyse financières
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
97.
DECENTRALIZED DATA MIXING FOR ANONYMOUS AND CONFIDENTIAL BLOCKCHAIN PAYMENTS, INCOGNITO COIN SWAPPING, AND HIDDEN WEIGHTED VOTING TECHNIQUES
The present disclosure provides a decentralized data mixing (DDM), a cryptographic scheme for non-interactive data mixing. The DDM scheme enables blockchain users to commit to specific data, and subsequently, utilize the encrypted version of this previously registered data across various blockchain applications without association to the original address that logged the data. DDM offers the following features: (i) no double redemption: a malicious user cannot redeem and use the same data twice; (ii) theft prevention: a malicious user cannot use data that is not registered by him; (iii) non-slanderabilty: a malicious user cannot prevent an honest user from using her data; and (iv) unlinkability: a malicious user cannot link a tainted data from an honest user to the corresponding mixed data.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
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 9/30 - Clé publique, c.-à-d. l'algorithme de chiffrement étant impossible à inverser par ordinateur et les clés de chiffrement des utilisateurs n'exigeant pas le secret
G06Q 40/02 - Opérations bancaires, p. ex. calcul d'intérêts ou tenue de compte
A computer is disclosed. The computer includes a central processing unit (CPU) configured to execute an operating system; and a security processing engine (SPE) coupled to the CPU, the SPE being on a same integrated semiconductor chip as the CPU and having dedicated hardware and dedicated software isolated from the CPU, wherein the SPE is programmed to boot and perform an integrity check for the CPU before the CPU executes an operating system.
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
H04W 4/80 - Services utilisant la communication de courte portée, p. ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
99.
METHOD, SYSTEM, AND COMPUTER PROGRAM PRODUCT FOR ARTIFICIAL INTELLIGENCE ASSISTED CYBERSECURITY THREAT MODELING TOOL
Methods, systems, and computer program products are provided for artificial intelligence assisted cybersecurity threat modeling tool that may include receiving data associated with a security architecture document for a specific software environment, converting the data associated with the security architecture document from a natural language format to a threat modeling data format, generating a plurality of vector embeddings based on the threat modeling data, identifying one or more potential cybersecurity threats based on the plurality of vector embeddings, and mapping the one or more potential cybersecurity threats to one or more corresponding controls that provide a potential mitigation action for the one or more potential cybersecurity threats.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
G06F 21/51 - 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 du chargement de l’application, p. ex. en acceptant, en rejetant, en démarrant ou en inhibant un logiciel exécutable en fonction de l’intégrité ou de la fiabilité de la source
G06F 21/44 - Authentification de programme ou de dispositif
Machine learning models for spatial-temporal forecasting systems based on a multi-layer perceptron (MLP) model or other feedforward network can incorporate one or more random projection layers. Such models need not compute or rely on information representing relationships between different spatial nodes. In addition, the model can include temporal mixer layers that process time series data in the frequency domain, thereby leveraging the periodicity of many spatial-temporal data series.
