167 results about "Security framework" patented technology

Guiding query creation for a generative artificial intelligence (AI)-enabled assistant, including: receiving, via a natural language interface for a security framework monitoring a cloud deployment, a natural language input comprising one or more entity identifiers; gathering information based on the one or more entity identifiers; providing, to a generative artificial intelligence (AI) model, a prompt based on the natural language input and comprising the gathered information; and receiving, from the generative AI model, a response to the prompt.

Architecture for a generative artificial intelligence (AI)-enabled assistant, including: receiving, via a natural language interface for a security framework monitoring a cloud deployment, a natural language input; selecting, by a delegator generative artificial intelligence (AI) model and based on the natural language input, a particular generative AI model from a plurality of selectable generative AI models; prompting the particular generative AI model based on the natural language input; and providing, via the natural language interface and in response to the natural language input, a response from the particular generative AI model.

The invention provides a risk defense method and device for jailbreak attack of a large language model. Risk defense is carried out from the input side, the model side and the output side of the large language model. The risk defense method comprises the following steps: S1, receiving input text information; s2, establishing a dynamic malicious keyword library on the input side of the large language model; s3, on the model side of the large language model, based on the training data transmitted in the step S2, training and learning model operation feedback information and model internal state information, and based on a dynamic adjustment strategy, adjusting the large language model; and S4, constructing an output auditing library on the output side of the large language model based on the pre-output text information transmitted in the step S3 and the dynamic malicious keyword library in the step S2. Through the cooperative work, the defense measures of each layer can play the maximum effect in the whole security framework, so that various potential attacks are effectively prevented and dealt with, and the overall defense capability of the model is jointly improved.

A decentralized artificial intelligence platform is disclosed that enables secure sharing and execution of AI modules in sensitive application domains. The platform comprises a knowledge module registry for discovering specialized AI modules, a security framework enforcing structural integrity of AI modules, a zero-knowledge proof validation service for verifying usage conditions without exposing private data, and a blockchain-based value chain for managing smart contracts and payments. In operation, an AI agent can fetch a required AI module from the knowledge module registry, prove the right to use it, execute the AI module on local data, and automatically pay the AI module's provider through a blockchain transaction.

Providing generative artificial intelligence (AI)-enabled notebook interfaces for a security framework, including: receiving a request to generate a notebook interface for a security framework monitoring a cloud deployment; generating, in response to the request, the notebook interface, wherein the notebook interface comprises one or more notebook cells for interacting with the security framework, wherein the one or more notebook cells comprise a natural language input cell for querying a generative artificial intelligence (AI) model; and presenting the notebook interface.

The invention belongs to the field of information technology and Internet of Things (IoT), and discloses a decentralized Internet of Things security framework system based on a block chain, and the framework specifically comprises a wallet component which is used for managing the identity of equipment, guaranteeing the uniqueness of each IoT equipment in a block chain network, and providing equipment private key storage and intelligent contract address association at the same time; the intelligent contract component is responsible for managing and distributing calculation tasks and realizing automatic processing of the tasks; the multi-layer security component is used for guaranteeing the security of identity authentication and data transmission of the IoT equipment; and the universal component is used for realizing the compatibility between an IoT equipment bottom layer module and a block chain application layer and providing a cross-platform universal interface. Through the embedded smart contract and a multi-layer security protection mechanism, data encryption transmission and multi-terminal task unloading are realized, the autonomy and security of IoT equipment are improved, and the security bottleneck of a centralized architecture is avoided.

A computerized system for dynamic cybersecurity policy using AI-based contextual adaptive learning includes an AI system that evaluates business contexts, risk tolerance, and productivity impact to generate threat intelligence assessments. The system includes a Contextual Adaptive Learning module that dynamically adjusts cybersecurity policies based on threat assessments to create security workflows. A Cybersecurity Mesh Development module that integrates policies across security frameworks. A Dynamic Scenario Catalog module that updates policy adjustments based on threat intelligence. An Automated Workflow Orchestration module that creates and refines security workflows for optimal efficiency. A Policy Recommendation and Automation module that generates prioritized security recommendations and automates policy changes based on organizational risk profiles and current security controls. This system harmonizes security policies while considering business context, risk, and productivity impacts.

A system and method for privacy-preserving communication validation and multi-attribute trust scoring is disclosed. The system analyzes communication metadata to determine pattern legitimacy by comparing current communication patterns against relationship fingerprints without accessing communication content. The system validates relationship context between communicating parties using interaction graph analysis and historical communication data. Cross-network intelligence correlation compares current patterns against aggregated patterns across voice, email, and messaging services, creating a self-strengthening security framework that recognizes emerging threat patterns while validating legitimate communication behaviors. The system generates comprehensive multi-attribute trust assessments comprising individual trust attribute scores including engagement rate, reliability index, channel preference, temporal pattern, and behavioral pattern, combined into overall trust levels. Trust context is displayed through a user interface presenting simplified, intuitive, and actionable information with progressive disclosure capabilities, enabling informed user decisions while preserving privacy. Communication processing actions provide users with appropriate engagement options tailored to specific trust assessment results.

The present application discloses a method, system, and computer system for obtaining responses to a query. The method includes: (a) receiving, at a sidecar, a communication for a data source, (b) determining, by the sidecar, a policy corresponding to the communication, the policy identifying a user-defined function (UDF) corresponding to the policy, the UDF being stored by the data source, and (c) invoking the UDF based on the policy using the sidecar.

The invention relates to the technical field of intelligent construction, and discloses an intelligent construction collaborative management platform and method based on digital twinning, and the method comprises the steps: firstly obtaining the practical operation data of a target engineering machine, analyzing the data safety level of the practical operation data to generate a distributed storage path, extracting storage node identifiers in the path, and deploying the storage node identifiers to a digital twinning platform; analyzing a node storage state index, querying a data backup demand and constructing a storage backup framework; then identifying an access request of the storage security framework, verifying a user identity, calculating an authority level index, analyzing an access range, and determining a platform multi-layer access regulation; then monitoring a permission change event, collecting a log, identifying a risk access behavior and calculating an access risk index; and finally, adjusting node encryption configuration according to the risk index, identifying an authority control key, and generating a self-adaptive security policy of the target engineering machinery on the platform. According to the invention, the integrity and safety of construction management can be improved.

The invention provides a data security privacy fusion method and system based on an industrial internet. Wherein a security framework is constructed based on the data stream subjected to differential privacy processing, and the security level of data in the security framework is defined; creating a decentralized identity authentication system for each participating entity through a block chain technology, and dynamically adjusting the access control authority of the identity authentication system according to the security level; establishing a data encryption and decryption rule according to the access control authority and the security level of the data stream, and applying the data encryption and decryption rule to the data stream; the encrypted data stream is transmitted to a cloud data center, and the security in the data transmission process is ensured by adopting a homomorphic encryption technology in the transmission process; generating a data fusion model in the cloud data center by using a result of the homomorphic encryption technology; and generating a final data security privacy fusion result according to the data fusion model. According to the technical scheme provided by the invention, the data security can be improved.

The invention discloses a security enhanced CAN (Controller Area Network) controller based on encryption authentication and intrusion detection, and aims to deal with security threats such as remote unlocking, starting and stopping of a vehicle by a hacker through the Internet of Vehicles. According to the invention, a security framework based on encryption authentication and intrusion detection is constructed, the pre-shared symmetric key is combined with the AES and HMAC-SHA256 algorithms, the encryption and authentication of CAN communication data are realized, and the confidentiality, integrity and authenticity of data transmission are guaranteed; meanwhile, an intrusion detection technology based on information entropy is introduced, and data frame injection attacks initiated through legal nodes are effectively defended. According to the method, a strategy of parallel processing of data frame transmission and encryption calculation is used, the problem that extra data carrying overhead is introduced due to the fact that a CAN controller and a security module are independently achieved in an existing method is solved, efficient transmission of CAN encrypted data is achieved, and the method has good development and application prospects.

A QR Code Verification Engine provides a multi-layered security framework for generating, validating, and authenticating QR codes while preventing tampering, fraud, and unauthorized access. The system embeds a hidden security layer within the QR code using steganographic encoding or invisible watermarking techniques, ensuring detection of any modifications. The hidden layer is encrypted using asymmetric cryptography, allowing only an authorized verification system to extract and validate it. An AI-powered tamper detection module analyzes QR codes for anomalies, while cryptographic hash verification ensures integrity. The system employs biometric authentication, push notification approvals, and contextual security measures to enhance user verification. Dynamic QR codes with expiration rules prevent replay attacks. Secure offline verification allows authentication without network connectivity. The system integrates with financial platforms, web security tools, and real-time fraud detection mechanisms, ensuring a highly secure and scalable QR code validation framework for transactions, identity verification, and access control applications.

The invention relates to the technical field of Internet of Things communication, and discloses a gateway management system and method based on multiple Internet of Things protocols, and the system comprises a processor architecture, a protocol conversion module, a collaborative management module, a unified security framework module and an edge computing module. The method is applied to the system. According to the application, efficient interconnection and dynamic collaborative management of multi-protocol equipment are realized through FPGA module hardware acceleration protocol conversion, a genetic algorithm and a Petr network hybrid task scheduling framework and a unified security mechanism irrelevant to a protocol, and various different mainstream Internet of Things protocols are compatible through a modular processor architecture and a dynamic expansion interface, so that the implementation is convenient, and the implementation is easy. According to the method, the hardware cost is reduced, rapid integration of a new protocol is supported, local and cloud resource allocation is further optimized through an intelligent switching mechanism of edge computing and cloud collaboration, the system stability and the data processing efficiency are improved, and the method is widely applied to scenes such as smart home, industrial Internet of Things and smart cities.

The invention provides a power transmission intelligent inspection image defect identification and intelligent marking system. The system comprises a data layer, an application layer, a system layer and a hardware layer. The data layer is used for managing storage data; the application layer is used for realizing a service logic and user interaction function; the system layer is used for managing an operation environment and a security framework; the hardware layer is used for providing underlying computing power, storage and communication support; according to the invention, multi-modal inspection data and multi-round time sequence analysis are fused, and an integrated intelligent inspection system with high-precision identification, trend perception and visual early warning capabilities is constructed.

A method for implementing a slice security zone (SSZ) in a 5G network. The method comprises storing by an SSZ function executing on a first network server an SSZ security profile of the SSZ in a secure storage function, receiving by the SSZ function from a slice management function a slice registration request comprising information relating to a slice security profile of a slice managed by the slice management function, if the slice security profile complies with the SSZ security profile, storing by the SSZ function a slice registration association between the slice and the SSZ in the secure storage function, and sending by the SSZ function to the slice management function a slice registration response comprising information relating to whether the slice was registered in the SSZ.

The invention discloses a WebRTC-based vehicle-mounted video stream secure transmission management method, and relates to the technical field of real-time communication, and the method comprises the steps: 1, constructing a hierarchical security system, and building a basic security framework; the layered security system comprises an application layer, a transmission layer, a network layer and a physical layer; 2, according to the basic security framework, in the WebRTC interactive connection establishment process, zero-knowledge proof is introduced, access strategy dynamic updating is achieved through a block chain, an authentication access control strategy set is output, and the authentication access control strategy set comprises device access, a bidirectional identity authentication rule and a block chain-based fine-grained access control strategy; 3, on the basis of the authentication access control strategy set, data security is guaranteed through hybrid encryption, the integrity of the Hash tree is verified, and an improved encryption transmission scheme is output; wherein the Hash tree is verified, and anti-jitter and code rate self-adaption are carried out in combination with the LDPC and the DRL.

The present invention introduces an artificial intelligence (AI) system that includes a model, a first model protection system, and a wrapper. The system is designed to enhance security by processing inputs and outputs through a protective layer. Specifically, inputs from users are initially directed by the wrapper to the first model protection system, which then hardens these inputs before they are fed into the model to produce outputs. Subsequently, the outputs are received by the wrapper and passed through the first model protection system again to harden the outputs before they are delivered to users. Additionally, the invention introduces a security assessment system for evaluating the potential risks associated with a target model before its deployment, comprising an assessment system, a red teaming system, and a second model protection system, collectively working to thoroughly assess and mitigate potential security threats. The present invention offers a comprehensive security framework for AI models, covering both the development and deployment phases, and addresses the escalating security challenges facing AI models.

A security framework for virtual machines is described. In one or more implementations, a hardware platform comprises physical computer hardware, the physical computer hardware including one or more processing units and one or more memories. The system also includes a virtual machine monitor configured to virtualize the physical computer hardware of the hardware platform to instantiate a plurality of framework-secure virtual machines. Further, the system includes a root framework-secure virtual machine instantiated by the virtual machine monitor. In accordance with the described techniques, the root framework-secure virtual machine is configured to control access to the hardware platform by the framework-secure virtual machines instantiated by the virtual machine monitor.

Systems and methods are disclosed to provide a security framework for the authentication of digital content and the prevention of unauthorized modifications, especially targeting the vulnerabilities introduced by deepfake technologies. It innovates by merging reverse engineering with expression manipulation detection to discern genuine from altered digital media. The process involves comparing historical data against synthetic or real-time content, generating a “video mesh” that enables precise manipulation identification. Enhanced by Smart Contracts for each content piece to record and verify changes, this system advances digital identity and transaction security significantly beyond current methodologies. Furthermore, it employs Generative AI within the Identity Intelligent Clip Reviewer to scrutinize blockchain-secured data for manipulation signs, issuing a Proof of Digital Manipulation (PODM) for verified authenticity. This comprehensive method ensures the integrity and trustworthiness of digital interactions across various platforms, marking a significant step forward in the protection against sophisticated cyber threats and unauthorized data alterations.

Techniques are described for generating visualizations of security framework information (such as, e.g., MITRE ATT&CK® information) displayed in connection with notable events detected by a data intake and query system. Data intake and query systems, SIEM systems, and other applications often provide user interfaces that display detected occurrences of incidents, sometimes referred to as “notable events,” within users' information technology (IT) environments. A data intake and query system is described herein that is capable of identifying notable events, assigning tactic and technique information to notable events (and optionally to associated risk objects), and causing display of tactic and technique visualizations which are intuitive and customizable, provide ready access to relevant documentation, and follow a format with which security analysts are familiar.

The invention relates to the technical field of power plant network access, and discloses a PCFT security framework-based new energy power plant network access security protection system, which comprises a security partition system, a firewall and logic isolation system, an encryption and authentication system, a PCFT security framework, an intrusion detection and host equipment reinforcement system and a security management platform, the security partition system is in communication connection with the firewall and logic isolation system, the firewall and logic isolation system is in communication connection with the encryption and authentication system, and the encryption and authentication system is in communication connection with the PCFT security framework. Therefore, the process of manually processing each resource access control is simplified, the PCFT security framework is used, the security of the system can be effectively improved, security vulnerabilities are reduced, the security management process is simplified, the availability, integrity and confidentiality of the system are ensured, and data are prevented from being modified or disclosed without authorization.

A system and method for security validation of incoming communications through relationship fingerprints is disclosed. The system analyzes metadata from incoming communications to identify communication patterns without accessing content. Using these patterns, the system validates relationship context between communicating parties through an interaction graph and relationship fingerprints stored in a database. The relationship fingerprints contain temporal patterns, channel preferences, and behavioral patterns that evolve as relationships develop. The system validates incoming communications by matching current patterns against stored relationship fingerprints. Additionally, the system enables cross-service pattern sharing through aggregated patterns that can be normalized and shared across networks while maintaining privacy. The system continuously updates both relationship fingerprints and aggregated patterns as new communications occur, creating an evolving security framework based on relationship patterns.

A system and method for encoding and decoding optical codes with context-aware, multi-level security. Input data is classified into security levels with associated context sensitivity requirements. The system compresses data using public and private codebooks based on security classifications, then generates optical codes incorporating both compressed data and context requirements. When scanned, the system collects environmental contextual data (location, network environment, device security, user behavior), analyzes it against embedded context requirements, and dynamically determines which security levels are accessible in the current environment. Only authorized security levels are decoded using appropriate codebooks based on both user credentials and current contextual factors. This approach enables fine-grained, context-sensitive access control that adapts to changing environments while maintaining the compression benefits and capacity advantages of the multi-level security framework.

Systems and processes are disclosed to monitor and control toxic configuration in software container deployment. AI-based monitor in each node provides end-to-end fault management system that can detect, diagnose, classify, and suggest remediation actions for non-virtualized cloud-based misconfiguration vulnerabilities. Anomalies are diagnosed using pre-computed fault signatures and automated remediation is integrated with a cloud management stack. Multiple monitoring layers within nodes secure the container-based virtualization environment. Container-based “CSTC security framework” virtualization technology provides security and identifies potential toxic configuration threats. CSTC security locates container-based systems at severe risk for DDOS attacks to kernel vulnerability / container breakout and ensures appropriate privilege configuration for user processes. Resource access limited based on policies and CSTC security profiles as well as provide AI-based monitoring of container runtime behavior to provide additional security layer that ensures safety and protection in container-based virtualization.

The present application relates to a file processing method and electronic device. The method includes: using a custom function implemented on the Endpoint Security framework to obtain the path name of the process used to open the current file and the path name of the current file; when it is determined that the process and the current file meet the preset conditions and the current file is an encrypted file, calling the es_respond_flags_result function provided by the Endpoint Security framework to set the process to not have the permission to open the current file; sending the path name of the process and the path name of the current file to the redirection service process; the custom function returns, and returns the processing operation of the current file to the process, triggering the process to generate the first prompt information of the failure to open the current file; decrypting the current file based on the redirection service process, and calling the process to continue to open the decrypted file. The present application solves the problem that there are limitations on the operating system's scheme for opening encrypted files, and it will cause the stability of the related application or operating system to decrease.

Systems and methods are disclosed to provide a security framework for the authentication of digital content and the prevention of unauthorized modifications, especially targeting the vulnerabilities introduced by deepfake technologies. It innovates by merging reverse engineering with expression manipulation detection to discern genuine from altered digital media. The process involves comparing historical data against synthetic or real-time content, generating a “video mesh” that enables precise manipulation identification. Enhanced by Smart Contracts for each content piece to record and verify changes, this system advances digital identity and transaction security significantly beyond current methodologies. Furthermore, it employs Generative AI within the Identity Intelligent Clip Reviewer to scrutinize blockchain-secured data for manipulation signs, issuing a Proof of Digital Manipulation (PODM) for verified authenticity. This comprehensive method ensures the integrity and trustworthiness of digital interactions across various platforms, marking a significant step forward in the protection against sophisticated cyber threats and unauthorized data alterations.

Methods and systems for securing distributed systems are disclosed. The distributed systems may include data processing systems subject to compromise by malicious entities. If compromised, the data processing systems may impair the services provided by the distributed system. To secure the distributed systems, the data processing systems may implement a security framework. The security framework may utilize a hierarchy that defines authority for validating trusted entities. The hierarchy may vest authority across the distributed system, and may be based on a reputation (e.g., weighted reputation) of each of the data processing systems within the distributed system. If the reputation of a data processing system meets criteria, the data processing system may be treated as being compromised and a local refresh of security data may be performed. Consequently, the impact of compromise of the data processing system may be limited by the distributed authority.

A method includes receiving multiple security framework requirements, mapping the security framework requirements to a predicate, mapping the predicate to a system-specific implementation, evaluating, using a runtime system, the target system by analyzing a multitude of build files using the system-specific implementation, and presenting a report indicating whether the security framework requirements are satisfied.