Abstract: In some aspects, a computing system may use a machine learning model to determine whether a computer security policy should be modified to reduce the likelihood of a cyber security incident. Through the use of a machine learning model, unsafe combinations of access grants or permissions may be identified and modified to prevent cyber security incidents from occurring. The computing system may input a representation of a computer security policy into a machine learning model, which has been trained on a dataset that includes representations of computer security policies. The computing system may generate output indicating a likelihood that the first computing system will be involved in a cyber security incident. Based on the output satisfying a first threshold, the computing system may generate a recommendation to modify the first computer security policy. The computing system may modify the first computer security policy based on the recommendation.

Abstract: A system and method are described that enables mobile devices (e.g. including but not limited to a mobile phone or the like), to intercept and respond to contactless card authentication requests, allowing mobile devices to be used in place of contactless cards. Enabling mobile phone devices to emulate contactless cards decreases issues related to lost or damaged cards, enabling a single device to be used to provide tokens related to multiple different contactless cards, and leverages functionality of the mobile device to provide dual-factor authentication.

Abstract: Systems and methods related to integrating blockchain functions with external systems using a variable non-fungible token. A variable non-fungible token comprises a non-fungible token that is minted with an indication of a non-transferable ownership wallet (e.g., a digital wallet for which the non-fungible token is minted for), a non-transferable smart contract address that has permissions for updating metadata for the variable non-fungible token, and a metadata property threshold based on a specific user corresponding to the digital wallet.

Abstract: Techniques to improve detection and security of images, including formation and detection of matrix-based images. A histogram may be used to determine a most prevalent color of a plurality of prevalent colors associated with an environment. A related plurality of colors may be determined based on the most prevalent plurality of colors and a colorspace conversion. A matrix barcode may be generated based on the related plurality of colors and an ultraviolet layer.

Abstract: Methods, systems, and apparatuses are described herein for generating and managing virtual transaction cards based on mobile device location so as to provide transaction security during in-person transactions. A geographic location of a mobile device may be determined, a proximate merchant may be selected, and a virtual transaction card may be generated for that particular merchant. Data corresponding to that virtual transaction card may be deployed into a digital wallet device for use during transactions with point-of-sale devices. Use of the digital wallet device may be conditioned on geographic location, time, an unlock command from a mobile device, or the like. By providing such dynamically-generated and limited virtual transaction cards for in-person transactions, the threat of security vulnerabilities relating to point-of-sale systems may be mitigated.

Abstract: An automated method is provided for validating an action based on beacon source proximity to a user device. A user data processing device receives from a remote action validation server an action validation request. The request includes identification of an authentication device that may include a beacon transmitter and identification of a proposed action associated with the authentication device. The user data processing device determines whether the authentication device is within beacon signal reception range of the user data processing device and transmits an action validation response to the remote action validation processing system.

Abstract: Techniques to utilize excess resources in a cloud system, such as by enabling an auxiliary resource utilizer to use resources while they are not needed to support primary resource utilizers, are described herein. Some embodiments are directed to identifying and allocating excess capacity of resources in a cloud system to auxiliary resource utilizers based on one or more policies. In various embodiments, excess resources in one or more of the set of resources in the cloud system, or cloud resources, may be determined based on monitoring utilization of the cloud resources by the primary resource utilizers. In many embodiments, an auxiliary resource utilizer that is in compliance with a set of utilization policies may be identified and the excess resources may be allocated to the auxiliary resource utilizer.

Abstract: Provided are transaction cards including an infinity mirror. In some approaches, a transaction card may include a body comprising a first reflective layer and a second reflective layer, and a light source between the first reflective layer and the second reflective layer.

Abstract: In some implementations, a user device may detect a communication associated with the user device and a user. The user device may analyze, using a machine learning model, a context of the communication to determine a risk score associated with the communication, the risk score indicating a likelihood that the communication is associated with a fraudulent actor attempting to solicit sensitive information from the user. The user device may monitor the communication to identify a trigger in the communication that indicates that sensitive information is to be shared, wherein monitoring the communication includes performing one or more operations to secure the communication based on the risk score satisfying one or more thresholds. The user device may detect, based on monitoring the communication, a portion of the communication that includes the sensitive information. The user device may obfuscate the portion of the communication.

Abstract: A method may include executing an entity resolution microservice programmed to receive an entity-specific data request for entity-specific data for an entity from a plurality of entities. An application programming interface (API) call is transmitted to an entity profile database that programs the entity profile database to identify entity-specific data in data records matching the entity-specific data in the entity-specific data request and transmit to the entity resolution microservice a compressed representation of the entity-specific data identified in the at least one entity profile database. The compressed representation may be received and the compressed representation may be transformed to an uncompressed representation. An entity-specific database query request for a search engine to perform a database search for additional entity-specific data is generated based on the uncompressed representation.

Abstract: Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second subset.

Abstract: Systems and methods are provided for authenticating an identity of a user requesting a resource or service from an entity. In some embodiments, a system may include at least one processor; and a non-transitory medium containing instructions that cause the system to perform operations. The operations may include receiving credential information associated with the remote user, and receiving, from the server associated with the entity, first hash information. The operations may also include generating second hash information based on information associated with the user, comparing the first hash information with the second hash information, and transmitting an indication based on the comparison to the server associated with the entity.

Abstract: A method of identifying and recognizing characters using a dual-stage neural network pipeline, the method including: receiving, by a computing device, image data; providing the image data to a first convolutional layer of a convolutional neural network (CNN); applying, using the CNN, pattern recognition to the image data to identify a region of the image data containing text; providing sub-image data comprising the identified region of the image data to a convolutional recurrent neural network (CRNN); and recognizing, using the CRNN, the characters within the sub-image data.

Abstract: Systems and methods for detecting interception devices. In some aspects, the system causes transmission of a first detection signal. Based on receiving a first response signal, the system determines a first probability of detection of a first interception device. Based on the first probability of detection, the system transmits a first command to deactivate a user authentication interface. The system may cause transmission of a second detection signal and determine a second probability of detection of a second interception device. In response to the second probability, the system may transmit a second command to reactivate the user authentication interface.

Abstract: Aspects provided may allow for a user to block charges from an entity without having to contact the entity. After detecting that the user has enrolled in a trial or subscription of an entity offering, the user may be provided with the option to block charges from the entity. Using incoming data, charges from the blocked entity may be identified and prevented from being applied to the user. Further aspects may provide for more discrete charge blocking, such as blocking charges for one activity while allowing other charges for different activities from the same entity to go through, and training an identification model that isolates the entity identifier from the incoming data and matches the entity identifier to known entities.

Abstract: A data security and fraud prevention system is configured to transmit a web form to a first device, receive through the web form first data including first user private data associated with a first user, receive a request to share the web form with a second user, create a cache storage and an unique identifier associated with the web form, and mask the first user private data to prevent access to the first user private data by the second user. The data security and fraud prevention system is further configured to encrypt the unique identifier, generate a share session between the first device and a second device associated with the second user, receive through the web form second data including second user private data associated with the second user, mask the second user private data to prevent access to the second user private data by the first user, and aggregate the first data and the second data to complete the web form.

Abstract: In some implementations, a redundancy system may receive, from a log storage, a plurality of log files that were generated by a plurality of monitoring programs. The redundancy system may apply a machine learning model to the plurality of log files to detect one or more redundancies. The redundancy system may determine at least one monitoring program, in the plurality of monitoring programs, that is a candidate for removal based on the one or more redundancies. The redundancy system may transmit, to a ticket system, a command to open a ticket associated with the at least one monitoring program.

Abstract: Systems as described herein may include detecting live browser information that a user navigates to a first website displayed in a first open browser tab and a second website displayed in a second open browser tab. A data sharing server may provide the live browser information to a machine learning model as input. Based on feedback from the machine learning model, one or more similar products displayed in the first website and the second website may be determined. The data sharing server may detect an update on the one or more similar products, and cause a user device to display an alert indicating the update on the similar products.

Abstract: A device may receive, from a user device, a transaction request associated with a first entity and identify a distributed ledger associated with the first entity, the distributed ledger including a set of blocks recording work data associated with the first entity. The set of blocks may include: a first subset of blocks including data specifying work performed by the first entity, and a second subset of blocks including data verifying a portion of the work performed by the first entity and specified by the data included in the first subset of blocks. The device may determine that a transaction, associated with the transaction request, is associated with the first subset of blocks and the second subset of blocks. Based on predetermined instructions that correspond to the transaction and the distributed ledger, the device may perform the transaction.