Abstract: Genetic algorithm testing of a target application includes sending attack utterances to a target application. Genetic algorithm testing further includes receiving, from the target application, application LLM responses generated by the target application and the application LLM responsive to the attack utterances. The application LLM responses are each linked to a corresponding attack utterance to form multiple pairs. Genetic algorithm testing further includes sending, to an evaluation LLM, at least one evaluation LLM prompt including the pairs, identifying, from the set of evaluation results from the evaluation LLM, at least two attack utterances that caused the target application to fail. Genetic algorithm testing further includes mutating the at least two attack utterances to generate a new attack utterance and testing the target application with the new attack utterance to update the set of evaluation results. Genetic algorithm testing further includes presenting the set of evaluation results.

Abstract: Various embodiments of the present technology generally relate to systems and methods for providing a Security Intelligence Automation (SIA) engine. The SIA engine provided herein may include multiple security test plug-ins configured to perform a security assessment on a plurality of Open System Interconnection (OSI) layers of a target application. In an aspect, a method includes determining, by the SIA engine, security inputs for security test plug-ins and generating, by the SIA engine, one or more templates based on the security inputs. Each of the templates may correspond to a respective security test plug-in. After the security inputs are determined and the templates generated, the SIA engine may perform the security assessment on the target application based on the one or more templates, and in some cases the security inputs. Responsive to performing the security assessment, the SIA engine may generate a report including results from the security assessment.

Abstract: An application executing on a processor may access a permissions database includes permissions data for a plurality of accounts. A large language model (LLM) executing on the processor may analyze, based on the permissions database, a plurality of operations associated with the plurality of accounts. The LLM may determine, based on the analysis, a first operation of the plurality of operations associated with a first account of the plurality of accounts. The LLM may generate, based on the first operation and the permissions data for the first account, modified permissions data for the first account.

Abstract: A method comprising training a predictive model system using historical data describing prior incidents that occurred in the communication network, wherein the historical data comprising prior incident data, prior subscriber usage data associated with the prior incidents, and prior performance data associated with the prior incidents, detecting an anomaly event based on current network parameters, wherein the anomaly event is an event or state occurring across one or more of network elements in the communication network that is indicative of a future incident that is likely to occur in the communication network, and instructing a remediation action to perform based on the anomaly event.

Abstract: Methods and systems for managing operation of a data processing system are disclosed. To manage operation of the data processing system, software compliance events may be identified by a management controller of the data processing system. Based on the identified software compliance event, the management controller may generate a virtual entity that hosts natively hosted applications of the data processing system and utilize an observability entity to determine whether required applications are identified in the natively hosted applications. Based on the determination, the management controller may manage installation of any required applications not hosted by hardware resources of the data processing system.

Abstract: Techniques for action correlation for multiple devices is described herein. In an example, a computer system determines first contextual data associated with a first device. The computer system determines second contextual data associated with a second device. The first device and the second device are associated with an account. The computer system generates, based at least in part on the first contextual data and the second contextual data, configuration data indicating a trigger to be detected by at least one of the first device or the second device and an action to be executed by at least one of the first device or the second device upon the trigger being detected. The computer system associates the configuration data with the account.

Abstract: A creation of a first process is detected in a kernel space of the operating system executing on a computing device. An exec parent of the first process is determined. The exec parent identifies a second process within an ancestry of the first process that last performed an exec operation prior to the creation of the first process. A unique process identifier (UPID) associated with a process identifier (PID) of the first process is generated. The UPID is associated with the exec parent in a first mapping store that maps the PID to the UPID. Process activity of the first process executing in the operating system is tracked to generate process activity data that comprises the exec parent.

Abstract: Systems, devices, and methods are provided for providing data clean room capabilities that allow for the export of privacy-preserving labels. A data clean room may be provisioned to obtain datasets from various parties. Code executing in the data clean room may select a differential privacy machine-learning model from a plurality of differential privacy machine-learning models train the selected differential privacy machine-learning model to infer noisy labels, determine a set of users of interest for a multi-party collaboration effort, infer, using the differential privacy machine-learning model, a set of noisy labels for the set of users, and determine an exportable dataset that comprises the noisy labels rather than private labels containing sensitive/private information.

Abstract: Portable electronic devices can be used to perform tracking functionality through the exchange of proximity messages. Based on the payload in these messages, a mobile device can detect whether a portable electronic device is likely performing unwanted tracking. The mobile device user may wish to identify an account that is associated with the portable device. In response to a request from the mobile device, the portable electronic device can provide a partial identifier that can be used to determine an associated account. The portable electronic device can also provide information that the mobile device can use to locate disablement instructions that can show how to stop the portable device from performing tracking functionality.

Abstract: A method of timestamping an item at a timestamping device is provided. The timestamping devices comprising a classical computing device and a quantum computing device. The method comprises at the classical computing device obtaining the item to be timestamped and determining an input token based on the received item. The method further comprises at the quantum computing device receiving a randomly generated quantum state from a verifier via a quantum channel wherein the randomly generated quantum state is received at time, t and wherein the method comprises using the timestamping device to combine the randomly generated quantum state with the input token to produce a timestamp proof token associated with the time, t.

Abstract: Aspects of the disclosure relate to mitigation and detection of steganographic modifications embedded in images. A computing platform may receive an image embedded with steganographic modifications. The computing platform may change or modify any number of bits of one or more color components of one or more pixels of an image, rendering the steganographic modifications ineffective. The computing platform may cause at an isolation zone system, execution of an image, including steganographic modifications, to identify images embedded with steganographic modifications. The computing platform may also compare an image with image stored in an image storage module. The computing platform may store an image from the image storage module with a highest visual comparison score rather than the image.

Abstract: Systems, methods, and storage media for creating an entity-oriented data fabric (EODF) for a protected environment (PE) are described, the system configured to identify a plurality of entities associated with the PE; obtain first data associated with at least one entity from the PE; identify a relationship with at least one other entity for each of the entities; create a plurality of objects, where each of the plurality of objects is associated with one or more entities and a portion of the first data; store first information related to the entities, first data, relationships, and the objects; create the EODF for the PE, the EODF comprises a data framework for providing a unified view of the plurality of entities and relationships, the EODF facilitates discovery of compromised entities or entities vulnerable to being compromised; and providing a visualization for displaying the first information on a user interface.

Abstract: A wireless communication method for use in network slice-specific authentication and authorization function is disclosed. The wireless communication method comprises storing a network slice-specific authentication and authorization, NSSAA, status comprising a plurality of records for a wireless terminal, and transmitting, to an access and mobility management function, AMF, the NSSAA status.

Abstract: Techniques are provided for validating edge computing devices using verification of network identifiers. One method comprises obtaining an ownership voucher for an edge device, wherein the ownership voucher comprises credentials of the edge device, wherein the edge device comprises an integrated circuit used by the edge device to access a network, such as a mobile network, and wherein the ownership voucher further comprises: (i) an identifier of the integrated circuit used to access the network and/or (ii) an identifier of the network; verifying, by a provider of the network: (i) the identifier of the integrated circuit and/or (ii) the identifier of the network; and automatically enabling the edge device to access the network based on a result of the verifying. The ownership voucher may comprise an identifier of a subscriber of the network and the provider of the network may verify the identifier of the subscriber of the network.

Abstract: Responsive to domain name server (DNS) flood conditions being detected, a fully qualified domain name (FQDN) of each DNS query is checked against a table of legitimate FQDNs, and DNS queries having FQDNs that are verified as legitimate queries to pass to the DNS server are allowed, and DNS queries having FQDNs not verified as legitimate queries from passing to the DNS server are blocked.

Abstract: A method includes placing a first hook on a page-executing function configured to execute a web page on a web server, and placing a second hook on at least one sensitive function. The first hook is configured to ascertain whether the page-executing function is called to execute a server-side script, and in response to the page-executing function being called to execute a server-side script, associate, with a current execution thread, data associated with the calling of the page-executing function and indicating that the page-executing function is called to execute the server-side script. The second hook is configured to ascertain whether the sensitive function is called from an execution thread associated with the data, and in response to the sensitive function being called from an execution thread associated with the data, output a message including the data. Other embodiments are also described.

Abstract: Deception-based techniques for responding to security attacks are described herein. The techniques include transitioning a security attack to a monitored computing device posing as a computing device impacted by the security attack and enabling the adversary to obtain deceptive information from the monitored computing device. Also, the adversary may obtain a document configured to report identifying information of an entity opening the document, thereby identifying the adversary associated with the attack. Further, the techniques include determining that a domain specified in a domain name request is associated with malicious activity and responding to the request with a network address of a monitored computing device to cause the requesting process to communicate with the monitored computing device in place of an adversary server. Additionally, a service may monitor dormant domains names associated with malicious activity and, in response to a change, respond with an alert or a configuration update.

Abstract: A system, method, and computer-readable medium enforce compliance, policy governance, and jurisdiction-aware control of digital artifacts generated by AI models. A deterministic digest of each artifact is stored in a registry, and a compliance token is generated encoding policy predicates, consent scope, jurisdictional lineage, monetization parameters, and a zero-knowledge proof component including a proof statement ID, cryptographic commitment, and verification key. A gateway verifier receives the artifact and token, verifies the signature, performs zero-knowledge proof validation without revealing regulated data, evaluates encoded policies, and renders a permit-or-deny decision. Verification results and compliance decisions are recorded via a dual-ledger atomic commit engine that updates both compliance and financial ledgers. A settlement engine calculates royalty values based on validated performance metrics and appends the results to the commit entry.

Abstract: The invention relates to a method for authenticating a user to access a web application, including reception, by an application server, of an access request; redirection to an IDAAS authentication server; authentication of said user with a social authentication server selected from said IDAAS server, reception by said IDAAS server of said user's personal data, verification of personal data, and when the personal data satisfies at least one web application access rule, transmission of a proof of authentication authorizing said user to access said web application. It also relates to a computer program and an authentication system implementing such a method.

Abstract: A system includes a memory configured to store instances of a software application executable on a computing device and a set of sensitive data and a processor operably coupled to the memory and configured to detect an interaction to initiate an execution of user interactions with the set of sensitive data. The processor is further configured to execute one or more generative machine-learning models trained to generatively present sequences of different decoy data to a user in response to an execution of interactions with the different decoy data, partition the set of sensitive data into sets of sharded sensitive data, and transfer the sets of sharded sensitive data to a trusted database and onto a trusted computing node. The processor is further configured to store a log of the generatively presented sequences of different decoy data and the execution of the interactions with the different decoy data.