616 results about "Secure state" patented technology

The invention relates to the technical field of network security situation generation, in particular to a network security situation generation method based on multi-view monitoring. The method comprises the following steps of: constructing a multi-view data acquisition system, acquiring real-time information from a multi-dimensional data source, and comprehensively capturing potential threats by utilizing an intelligent sensing technology; cleaning, noise filtering and feature extraction are performed on the acquired data based on a dynamic threshold self-adaption multi-factor cleaning method, so that the accuracy and consistency of the data are ensured; a dynamic analysis algorithm based on deep learning is adopted, the incidence relation between the security events is mined, and the development trend of potential threats is predicted; constructing a joint learning model, and comprehensively evaluating the security state of the network environment; the security situation is dynamically displayed by using a visualization technology, and a security policy is quickly generated in combination with an automatic early warning and response mechanism to resist threats. According to the method, accurate evaluation and prediction of the network security situation are realized, and support is provided for security decision-making in a complex network environment.

The invention relates to the technical field of network security, in particular to a network security big data state evaluation method based on pattern recognition, which comprises the following steps of: extracting multi-modal features from a network flow log, a system event log, a host behavior log and threat intelligence data, generating a feature matrix, performing feature dimensionality reduction by adopting an auto-encoding network, and obtaining a network security big data state evaluation result; carrying out attack behavior classification and abnormal mode identification in combination with unsupervised clustering and a graph neural network; constructing an attack transition probability matrix based on a Markov model; forming a time sequence attack chain; predicting an attack development trend; and a dynamic protection instruction is issued to the safety equipment. According to the method, the unknown attack detection capability can be improved, the time sequence attack traceability is enhanced, the security situation assessment is optimized, and the method is suitable for security situation awareness in cloud computing, industrial internet and large-scale network environments.

The invention discloses an SCL field safety accident analysis and early warning method and system, a medium and a program product, and the method comprises the steps: carrying out the distributed cleaning and feature extraction of multi-source heterogeneous monitoring data, and obtaining a multi-dimensional time sequence feature flow; constructing a dynamic association network of a security state; identifying a key influence factor chain, and establishing a semantic analysis model; constructing a safety threshold system; evaluating the multi-dimensional time sequence characteristic flow by using a safety threshold system; when the multi-dimensional time sequence characteristic flow triggers early warning, performing tracing analysis by using a semantic analysis model to obtain a root event triggering the early warning, and simulating the development trend of the root event based on a preset evolution model; determining a predicted risk range and a risk type according to the tracing cause analysis result and the accident development trend; and the corresponding accident early warning scheme is matched in the preset database according to the risk range and the risk type, and the accident early warning scheme is sent to the monitoring terminal, so that the accuracy of judgment and classified early warning of different types of safety accidents is improved.

The present disclosure provides a system for secure compute using artificial intelligence agents. The system includes a hardware execution environment with one or more computerized processors and electronic storage media. The processors are configured to establish a secure agent comprising a secure state management module, an encrypted state transition management module, a threshold cryptography implementation, and a digital signature verification module. The system also includes a plurality of atomic agents, each configured to perform a composite task and comprising a task-specific execution module, a state management interface, and a communication module. An orchestrator agent coordinates secure execution of the atomic agents and includes a task distribution module, a result aggregation module, a workflow management module, and a security policy enforcement module. The orchestrator agent integrates encrypted outputs from the atomic agents to perform composite tasks while maintaining data integrity and security through the secure state management module.

The present invention provides an elevator emergency rescue decision-making method and system based on reinforcement learning, which relates to the technical field of elevator emergency rescue, including real-time collection of elevator multimodal data through a distributed sensor network to generate an elevator state representation vector; inputting the obtained elevator state representation vector into a pre-trained graph convolutional neural network model, and simultaneously starting an edge computing unit for real-time simulation, simulating system responses under different rescue strategies, evaluating the feasibility of each rescue strategy, weightedly fusing the multi-dimensional risk score and the rescue strategy feasibility evaluation results, and generating a risk assessment report; sending a rescue instruction set to an elevator emergency rescue executive agency through a secure encrypted channel, and continuously monitoring the real-time feedback information of the elevator emergency rescue executive agency, and triggering a decision re-evaluation mechanism when an abnormal situation occurs, until a passenger safe evacuation signal is received and the elevator system restores a safe state signal, and the rescue mission is completed.

The invention belongs to the technical field of computer data protection, and particularly relates to a computer data hierarchical protection method and a dynamic protection system. According to the method, the to-be-protected data is graded and scored, dynamic adjustment of the data protection grade is realized in combination with the dynamic risk of the computer network environment, and more detailed data grading is performed in combination with the semantic risk value by identifying sensitive information in the to-be-protected data, so that the pertinence and effectiveness of data protection are ensured, and the data protection efficiency is improved. Meanwhile, multiple risk parameters of the computer network environment are comprehensively considered, the security state of the network environment is reflected in real time through calculation of the dynamic risk score value, the data protection grade is intelligently adjusted according to the grading score and the dynamic risk score value, and dynamic optimization of the data protection strategy is achieved; and through fusion of historical behavior records and current session contexts of operators, fine management of access permissions is realized, and the security of data access is further enhanced.

The invention relates to the technical field of Internet of Things, and discloses a multi-factor dynamic authentication Internet of Things network security access platform, which adopts a multi-factor authentication mechanism, combines biological characteristics, behavior characteristics and environment characteristics of equipment, performs identity verification through biological recognition, equipment fingerprints and behavior analysis, and utilizes a dynamic authentication strategy. Detecting an abnormal IP behavior and triggering a security policy by adopting a dynamic IP binding technology, combining with equipment fingerprint identification and learning and analyzing an equipment network behavior mode; a dynamic key management mechanism is adopted, and keys are automatically generated, distributed and updated according to different devices, application scenes and communication requirements; machine learning and artificial intelligence technologies are utilized to comprehensively analyze historical access data, abnormal behavior modes, environment security states and the like of equipment, and the security risk of equipment access is automatically evaluated if suspicious equipment is detected. The method has the advantage of improving the security of the Internet of Things.

The invention relates to the technical field of network security, in particular to a cloud data secure transmission system and method based on a quantum encryption technology. Comprising a quantum key generation and management unit used for generating a physical layer security key, realizing key true random generation through a quantum state unclonable principle, and optimizing key negotiation efficiency by adopting an improved adaptive basis vector matching algorithm; a data transmission encryption unit; a physical layer safety monitoring unit; and a channel fusion switching unit. According to the method, the physical layer security key is generated based on the quantum state unclonable principle, the dependency limitation of a traditional encryption algorithm on mathematics is broken through, and the cracking risk of quantum computing on bottom layer encryption logic can be reduced; according to the invention, photon polarization state parameters are collected in real time through the physical layer security monitoring unit, the eavesdropping behavior is detected based on the preset error rate threshold, real-time perception of the eavesdropping behavior in a transmission link is realized, and the defect that the security state of the physical layer cannot be perceived in real time in a traditional scheme is overcome.

The invention provides an elevator safety intelligent monitoring method and system combining the Internet of Things and AI, and the method comprises the steps: obtaining a real-time sensing data set collected by a plurality of Internet of Things sensors, and carrying out the preprocessing operation, so as to generate a standard sensing data set; the pre-trained elevator state analysis model is used for carrying out feature extraction and safety state evaluation on the standard sensing data set, the real-time running state of the target elevator can be comprehensively and accurately reflected by integrating multi-source sensing data, evaluation deviation caused by single data or non-standard data is avoided, and the safety of the elevator is improved. An equipment maintenance optimization strategy is determined according to the safety state evaluation result, and a maintenance instruction set is generated to trigger maintenance operation execution, so that intelligence, automation and precision of elevator safety monitoring and maintenance are realized, the probability of elevator safety accidents is effectively reduced, the safety and reliability of elevator operation are improved, and the safety and reliability of elevator operation are improved. The manual inspection cost and the maintenance blindness are reduced, and the elevator maintenance management efficiency and quality are improved.

The invention relates to the technical field of blockchain network security monitoring, and particularly discloses a blockchain-based network security monitoring method and system, the system collects transaction data, block data and intelligent contract execution results from a plurality of blockchain nodes, the analysis technology calculates the abnormal degree of each time window, the change rate of data inconsistency is quantified, and the data security monitoring accuracy is improved. If a relatively high data inconsistent change rate is detected, further comparing consensus results of the nodes, calculating consensus verification differences of the nodes, identifying the nodes deviating from normal consensus behaviors, constructing a machine learning model of a support vector machine, evaluating the safety states of the nodes, and according to a result output by the model, determining the inconsistent change rate of the nodes. The safety states of the nodes are divided into normal, slight abnormality and serious abnormality, for the nodes marked as slight abnormality, the system analyzes the abnormality trend and deviation of the nodes through a time sequence, automatically marks high-priority concerned nodes and generates a review task list to remind an operator to intervene.

A method for managing a storage system includes initiating, by a hardware resource manager, a boot-up of a storage controller managing the storage system comprising a plurality of storage devices, making a determination, by the storage controller, that the storage controller is in a secured mode, based on the determination: identifying a security state of each of the plurality of storage devices, determining that a storage device of the plurality of storage devices is in an unsecured state, and based on the unsecured state, sending, by the storage controller, a security operation request for securing the storage device, obtaining a secure state response from the hardware resource manager corresponding to securing the storage device, and based on the secure state response, resuming operation of the storage controller based on the secure mode.

The invention relates to the technical field of quantum key distribution, and discloses a communication protocol security verification method based on quantum key distribution, which comprises the following steps of: establishing a quantum communication channel framework, loading protocol parameters to generate an initial security verification model, configuring a security state transition rule, and performing cross-layer data fusion in combination with quantum entity parameters; and obtaining a whole-process safety tracking model. And executing security path deduction through the model, generating a key exchange trajectory chain, constructing security trajectory simulation data, establishing a quantum conflict resolution mechanism, training and generating a security policy optimization model, and outputting security governance parameters. Security increment simulation information is generated based on security governance parameters and the like, a multi-target decision model is constructed in combination with protocol evolution constraint conditions, optimal security path parameters are adjusted and generated, a security verification strategy is verified and updated through a real-time quantum mapping network, and a whole-process security matching target is achieved. According to the method, the comprehensiveness, the accuracy and the dynamic adaptability of quantum communication protocol security verification are effectively improved.

The invention relates to a security state evaluation method and device of a network environment, equipment and a storage medium. The method comprises the following steps: acquiring security monitoring data generated by a plurality of data sources in a network environment; the security monitoring data comprises log data, flow data and vulnerability data; extracting security features from the security monitoring data; the security features comprise statistical features, time sequence features and semantic features; inputting the security feature into a security situation model, determining security assessment index values of multiple dimensions according to the security feature through the security situation model, and determining a security situation assessment result of the network environment according to each security assessment index value; and matching the security situation assessment result with the network security compliance rule to generate a network security compliance analysis result of the network environment. By adopting the method, the security state evaluation accuracy of the network environment can be improved.

The invention belongs to the technical field of neural network model security, and discloses a hierarchical encryption neural network model encryption method and system, and the method comprises the steps: obtaining model architecture data, hierarchical topology data and weight parameter data; constructing a model hierarchy sensitivity map for vulnerability analysis to obtain a key horizon map; constructing a parameter importance network for sensitivity analysis to obtain a core parameter set; constructing a model protection strategy knowledge base; performing equipment fingerprint analysis to obtain equipment unique identification data; performing matrix transformation detection to obtain a hierarchical transformation function family; generating a hierarchical key pedigree; performing hierarchical encryption analysis to obtain a hierarchical encryption matrix; performing hierarchical protection conversion by using the hierarchical encryption matrix to obtain a model protection version; performing multi-dimensional integrity verification to obtain a target encryption model; monitoring the operation safety state of the model in real time, and optimizing a hierarchical encryption matrix; and the safety of the model is greatly improved.

The invention discloses a multi-device collaborative management and optimization system based on a soft bus, and the system comprises a device access recognition module which is used for scanning known devices and unknown devices through the soft bus and a plurality of communication protocols, and configuring a drive program; the collaborative task scheduling module is used for receiving a task request sent by a user, obtaining a task allocation scheme according to the task request and the comprehensive score of the access equipment, monitoring the execution condition of the task allocation scheme and performing dynamic adjustment; the resource management optimization module is used for endowing a resource attribute value to the access equipment and optimizing a task allocation scheme in combination with the task request; the security protection module is used for verifying identities of the access equipment and the user, performing encryption and integrity verification on transmission data, performing classified storage, and monitoring a security state of the access equipment; and the user experience enhancement module is used for setting a unified operation interface and dynamically adjusting the operation interface to realize synchronous execution of equipment tasks and unified display of prompt information. And the multi-device cooperation capability and the user experience are improved.

The invention provides a thermal power network security consensus verification method and system based on artificial intelligence, and relates to the technical field of network security, and the method comprises the steps: collecting thermal power network equipment data, carrying out the feature extraction, inputting a deep neural network model, and carrying out the analysis, thereby obtaining a network security state evaluation result. Constructing a consensus mechanism based on a block chain technology, and storing an evaluation result to a plurality of nodes; when an evaluation result triggers a threshold condition, an improved practical Byzantine fault-tolerant consensus algorithm is started for verification, a credibility weight mechanism is introduced into the algorithm, and a credibility score is calculated according to node historical behaviors to serve as a voting weight. And an evaluation result exceeding two-thirds weighted voting is confirmed as a valid result, and safety early warning information is generated and broadcasted to all the control units. The accuracy and reliability of thermal power network security state evaluation can be effectively improved, security threats can be found and early warned in time, and the security protection capability of the thermal power network is enhanced.

Methods and systems for managing a data processing system are disclosed. A management controller of the data processing system may provide a sanitization request to a policy management server using an out-of-band communication channel. The management controller may obtain a response to the sanitization request from the policy management server via the out-of-band communication channel. The response may indicate whether performance of a sanitization process is authorized. The authorization may be based on a sanitization policy that governs sanitizations for the data processing system. If performance of the sanitization process is authorized, then the management controller may initiate and / or perform an action set based on the sanitization policy in order to complete the sanitization process, thereby placing the data processing system in a safe state.

The invention discloses a network space security intelligent monitoring and analysis system, and relates to the technical field of network security monitoring and analysis, and the system comprises a multi-source data collection module which collects multi-dimensional data in a full-link manner, and the collection frequency is dynamically adjusted along with a network load; the data preprocessing module cleans the fused data and generates a standardized analysis data set; the AI intelligent risk identification module identifies various safety risks in real time through a mixed deep learning model; the real-time response processing module starts differential processing according to a three-level mechanism; the threat traceability analysis module traces an attack link and generates a report; the security situation visualization module displays the security state in multiple dimensions; the data encryption storage module encrypts and protects data and performs double backup; and the system self-optimization module dynamically optimizes the strategy through incremental learning. The method is accurate in risk identification, timely in response processing, reliable in traceability and evidence storage, and efficient in cross-domain cooperation; terminal protection and third-party access control are enhanced, and network space security and stable service operation are comprehensively guaranteed.

The invention discloses a security resource allocation method for a low-altitude economic unmanned aerial vehicle semantic communication network, which relates to the technical field of wireless communication network resource allocation and comprises the following steps: acquiring communication data and network state sensing data of each node in an unmanned aerial vehicle network; performing semantic analysis on the communication data, determining semantic importance and setting a transmission priority; monitoring a security state based on the network state sensing data, identifying a potential security threat and determining a threat level; establishing a security constraint condition set according to the threat level and the semantic importance; establishing a multi-objective optimization model, and performing optimization allocation on network resources under the security constraint condition set; performing hierarchical processing and resource scheduling on the communication task based on the transmission priority and the optimal distribution result; and monitoring a resource allocation effect, and triggering resource reallocation when the performance index deviates from a threshold value. According to the method, adaptive resource allocation considering communication efficiency and safety protection is realized, and the overall performance of the unmanned aerial vehicle semantic communication network is improved.

The invention discloses an SM2 collaborative signature and encryption and decryption system and method fusing anti-quantum characteristics, and relates to the field of cryptography and information security. According to the method, an anti-quantum cryptographic algorithm and a national cryptographic SM2 cooperative computing framework are deeply integrated, and a key security system is constructed: SM2 sub-private keys, anti-quantum key pairs and public keys are acquired and generated through an anti-quantum algorithm software and hardware enhancement module, and the private keys are encrypted and stored and are regularly alternated; on the basis of anti-quantum collaborative signature, encryption and decryption modules, an anti-quantum verification mechanism is embedded, and data is transmitted in combination with a national secret TLCP protocol, so that signature, encryption and decryption operations are completed; the equipment integration and dynamic security control unit monitors a security state, calculates a threat index to generate a protection strategy, and dynamically switches a security mode, so that the problems of insufficient security, vulnerability to attacks and data tampering of a traditional SM2 algorithm under the threat of quantum computing are effectively solved; and the long-term anti-attack capability and the operation reliability of the equipment in a high-security demand scene are remarkably improved.

The invention provides a cross-domain attack defense method based on a game strategy. The method comprises the following steps: constructing a joint state space, and discretizing a joint norm of the joint state space; designing action spaces of an attacker and a defender, and performing factorization strategy design on the action spaces of the attacker and the defender; designing a revenue function for calculating the revenue obtained by the defender for defending; establishing a cross-layer coupled state transition model based on the combined residual variation trend of the combined state space; and formalizing the state transition model into a zero sum game, solving Nash equilibrium of attacker income and defender income, and outputting a defender strategy during Nash equilibrium as a defense strategy. When the method is applied to cross-domain attack defense, the design of the security state, defense strategy and action space of the information physical system can be clearly quantified by unified state modeling while the cascade reaction is considered, and the revenue function is designed to quantitatively guide the optimal defense decision, so that the effectiveness and robustness of cross-layer defense are improved.

The invention relates to the technical field of front-end application development, in particular to a micro-front-end architecture-oriented cross-application state management, style isolation and resource collaborative loading method, which comprises the following steps of: constructing a state management module, establishing a unified state communication protocol based on a publishing / subscribing mode, and realizing safe state synchronization through an authority control mechanism; a style isolation module is constructed, a Shadow DOM and CSS rule rewriting double isolation strategy is adopted, dynamic style elements are automatically processed, and the problem of style pollution is thoroughly solved; constructing a resource coordinator module, and realizing dependent intelligent management and multi-version coexistence based on semantic version specifications; and the configuration management center uniformly coordinates the work of each module. According to the method, safe communication, reliable isolation and efficient resource utilization between micro front-end sub-applications are realized, three core problems of difficult state management, pattern conflict and resource redundancy in the prior art are solved, and the maintainability, the stability and the development efficiency of a large front-end project are remarkably improved.

The invention discloses a data security management method and device based on dynamic encryption and real-time anomaly detection, and the method comprises the steps: obtaining data from a diversified data source, and obtaining standard data; dynamically encrypting the standard data to obtain encrypted data; performing feature extraction on the encrypted data to obtain data stream features; performing anomaly detection processing on the data stream features by using a detection engine to obtain a detection result; when the detection result is normal, marking the encrypted data as a safe state, and storing the encrypted data into the distributed nodes; when the detection result is abnormal, the danger is handled according to the confidence score, and a danger assessment result is obtained; and according to a risk assessment result, optimizing parameters of the detection engine, and generating a log. Therefore, the problems of static encryption failure, detection lag, response stiffness and the like in the prior art are effectively solved.

The present application relates to the technical field of communication security, and provides a packet inspection method, an electronic device, a system, and a computer-readable storage medium. In the present application, inspection mark information used for performing risk indication on a service packet is set in the service packet. In the process of forwarding the service packet in a forwarding path, a security device forwards the service packet carrying the inspection mark information, or performs security inspection on the service packet before forwarding and then updates the value of a field in the service packet on the basis of an inspection result. A network device sends flow security state information to a network management analyzer on the basis of the inspection mark information carried in the service packet. The present application can assist a control plane in identifying a service flow forwarding path having a risk.

Described herein are systems, methods and instrumentalities associated with a trustworthiness evaluation framework for determining the trustworthiness of a wireless transmit / receive unit (WTRU) to participate in a network operation such as an artificial intelligence machine learning (AIML) operation. The framework may provide capabilities for monitoring, evaluating, and / or selecting the WTRU to participate in the network operation. The trustworthiness of the WTRU may be evaluated based on data and / or analytics such as the privileges and security state of the WTRU, security policy rules, the behavior history of the WTRU, the attributes and / or reputations of the WTRU, referrals for the WTRU from other entities, etc. A trustworthiness level or score may be determined to indicate the trustworthiness of the WTRU. An access policy may be dynamically formed and / or enforced to reflect the trustworthiness of THE WTRU.

The invention relates to the field of Internet of Things technology, data analysis and insurance claim settlement, in particular to a security Internet of Things and insurance claim settlement intelligent evaluation integrated system, which comprises a security state data acquisition module, a dynamic security portrait module, an accident traceability and responsibility intelligent division module and an automatic claim settlement evaluation module. According to the method, deep analysis of multi-source heterogeneous environment data and accurate representation of the safety state are achieved, the dynamic safety portrait module can capture the essential topological structure relation of the data by constructing the functions of topological feature extraction, state representation, multi-scale anomaly detection, risk prediction and the like, and high-precision recognition and risk prediction of gradient anomaly are achieved. After an accident occurs, a complete accident data chain can be constructed, the responsibility proportion of each party can be intelligently divided based on objective data, and the compensation amount can be automatically calculated, so that full-process automation from safety monitoring to insurance claim settlement is realized, the anomaly detection accuracy is greatly improved, and potential risks can be found in advance.

The invention provides a honeypot configuration method based on a graph neural network. The honeypot configuration method comprises the following steps: collecting network situation data; calculating a node connection relation carried by edges of a network situation map according to the network situation data, and constructing a node feature vector to construct the network situation map; performing graph embedding processing to obtain a first feature matrix for representing node vectors in the graph; inputting the network situation map and the first feature matrix into a graph neural network, extracting node information and pooling feature expression of the node information by the graph neural network, reading node features obtained by each processing module, and splicing the node features obtained by the C processing modules to form a second feature matrix for performing security state classification and prediction on the nodes; and judging an attack situation according to the network situation maps at different time points, and generating a honeypot deployment strategy for the attack situation for adjusting honeypot resource configuration. By applying the method, the deployment strategy of the honeypot can be dynamically adjusted, and the change of a network environment and complex attack behaviors can be quickly responded.

The embodiment of the invention relates to the technical field of power system access safety control, and provides a power system access control method and device, electronic equipment and a medium, and the method comprises the steps: collecting equipment evaluation data of target access equipment, system evaluation data of a target power system and network risk evaluation data in real time, the target access equipment is equipment of a to-be-accessed target power system; performing equipment credibility evaluation on the target access equipment based on the equipment evaluation data, performing system resource environment evaluation on the target power system based on the system evaluation data, and performing network credibility evaluation on the security state of the current access network based on the network risk evaluation data; generating a target access control strategy based on the equipment trust evaluation result, the system resource environment evaluation result and the network trust evaluation result; and performing access control on the target access equipment based on the target access control policy. The flexibility, security and real-time response capability of access control are improved.

The invention discloses an information security protection system and method, and relates to the technical field of information security protection, and the system comprises a behavior modeling module which is used for collecting and standardizing terminal operation behaviors, and constructing a dynamic behavior chain model; the risk assessment module performs real-time risk analysis based on the behavior chain and outputs a grading result; the access control module dynamically adjusts access authentication and authority configuration according to the risk level, and intercepts abnormal access; and when an abnormal mode or a high-risk state is detected, the abnormity repairing module automatically formulates a repairing decision and executes a repairing operation to recover the safety of the equipment. According to the method, the identity verification mode and the permission configuration strategy of the access request are dynamically adjusted according to the risk level, the resource access boundary can be flexibly controlled in different security states, and better effects are achieved in the aspects of security, accuracy and timeliness.

The invention belongs to the technical field of power networks, and particularly relates to a power network vulnerability analysis system and method based on virtual attack and defense deduction, and the system comprises a data collection module which is used for collecting various data of a power network, the various types of data comprise network topology structure data, equipment configuration data, operation state data and security log data; and the threat intelligence integration module is used for collecting and integrating global network security threat intelligence and establishing a data interface with a threat intelligence platform to realize automatic synchronization and updating of the threat intelligence. Through continuous virtual attack and defense deduction, an attack and defense strategy is optimized in combination with a machine learning algorithm, a novel attack means can be simulated, and the power network security state can be monitored in real time. Even if an unprecedented attack mode appears, potential threats can be quickly identified through attack and defense confrontation, the discovery capability of novel and unknown vulnerabilities is greatly improved, and network security risks are responded in time.