513 results about "Secure state" patented technology

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 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.

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 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.

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 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.

The invention provides a data storage security monitoring method and system, and belongs to the field of data storage security, and the method comprises the steps: carrying out the multi-dimensional statistical feature extraction of historical operation feature data of a storage system, and constructing a historical security feature vector set; real-time operation feature data of the system is obtained, multi-dimensional semantic feature extraction is carried out, and a real-time security feature vector set is generated; by innovatively adopting a metric learning algorithm, the semantic distance between real-time and historical feature vector sets is calculated, and the abnormal deviation degree of the system is accurately determined. Based on the abnormal deviation degree and a predefined risk classification rule, the method dynamically evaluates the risk level of the storage system. And when the risk level reaches an early warning threshold value, the system automatically generates a safety risk early warning and executes a corresponding grading risk relief operation according to the risk level. According to the method, the security state of the storage system can be monitored in real time, potential risks can be actively identified, and the security protection capability of the data storage system is improved.

The invention discloses a vulnerability measurement method and device based on a trusted cloud platform and electronic equipment, and relates to the technical field of cloud security. The vulnerability measurement method comprises the steps that under the condition that it is detected that an application program on the trusted cloud platform is loaded, static measurement is conducted on the process of the application program, and a measurement value is obtained; comparing the measurement value with a reference value of an application program pre-stored in a preset reference library to obtain a comparison result, and under the condition that the comparison result indicates that the measurement value is equal to the reference value of the application program, dynamically measuring the process of the application program to obtain a dynamic measurement result, and under the condition that the dynamic measurement result meets a preset security semantic rule, determining that the application program is in a security state, and under the condition that measurement of all application programs on the trusted platform is completed, completing vulnerability measurement of the trusted cloud platform. According to the method and the device, the technical problem of relatively low accuracy of vulnerability measurement on the trusted cloud platform in related technologies is solved.

The invention relates to the technical field of power system safety, and discloses a safety early warning method and system for a power system data center. The method comprises the steps that a safety monitoring period threshold value is set, when the continuous operation duration of the data center reaches the standard, historical and real-time safety state summaries are synchronously obtained, the historical operation duration comprises historical operation duration and configuration parameters, and the real-time safety state summaries comprise current operation duration and configuration parameters. And searching a security data fluctuation set by calculating security difference measurement of corresponding parameters of the two types of summary. And when the set variation degree is greater than or equal to a variation threshold value, taking the time distance ratio between the data storage starting point and the historical acquisition point as well as between the data storage starting point and the current time point as an early warning trigger factor, and starting a safety data early warning response from the data storage starting point according to the factor. According to the method, historical and real-time data comparison is combined, accurate monitoring of the safety state is achieved, timely risk identification is assisted, and a safety barrier is built for operation of the data center.

The invention provides a data security protection system based on a reinforcement learning large model, and relates to the technical field of data processing, comprising the following steps: associating a historical attack chain feature library to extract corresponding attack behavior sequence features; fusing the knowledge-based data entity, the real-time environment baseline offset and the historical attack chain features to construct a comprehensive security state representation body; generating a protection strategy instruction set from the safety state representation body through a pre-training reinforcement learning large model; deploying a protection strategy instruction set in the zero-trust architecture, and collecting strategy effective time delay, a security entropy change gradient and a defense efficiency index to generate a feedback tensor; and constructing a reward function based on the feedback tensor, and updating strategy network parameters of the reinforcement learning model by adopting a near-end strategy optimization algorithm to form a closed loop. According to the invention, the intelligence, dynamic nature and adaptability of data security protection are improved.

Various aspects of the present disclosure relate to a network repository function (NRF) that receives a first signaling as a network function (NF) request from a NF, the NF request including a NF type, a NF identifier (ID), and NF security state information. The NRF verifies a NF security state based on the NF ID and the NF security state information. The NRF transmits a second signaling as a NF response, where the NF response includes a security verification of the NF request.

The invention discloses a control method of an electricity utilization information acquisition terminal with security situation awareness, and relates to the technical field of electricity utilization information acquisition. Multi-source state evaluation, command risk division, rule decision and execution feedback are no longer independent functions through operation modes, joint security state levels, control quotas, command risk levels, command quota state marks and mutual reference between local execution consistency indexes and collaborative domain execution consistency indexes. A technical system with a close coupling relationship is formed in the electricity utilization information acquisition terminal, so that the method is not only suitable for resident courts, special transformer users and important user scenes, but also capable of automatically updating operation mode definitions, safety state division thresholds, control quota parameters and safety control rules through version comparison after main station side strategy update messages are issued. And the terminal security control capability is continuously evolved along with operation experience and strategy adjustment, and a strong synergistic effect is embodied.

The invention relates to the technical field of traffic engineering facility monitoring, and particularly discloses a traffic engineering facility safety state monitoring system and method based on the Internet of Things, and the method comprises the steps: deploying distributed intelligent sensing nodes comprising multiple types of sensors and edge calculation units at key monitoring points of facilities; nodes collect data by adopting a dynamic self-adaptive sampling mechanism, and an edge computing unit preprocesses the data and performs preliminary abnormity early warning; the data is transmitted to a cloud platform through a hierarchical communication network; the cloud platform performs deep analysis by using a federated learning safety evaluation model, and calculates a safety index to generate an evaluation report; and when the monitoring value exceeds the threshold value, four-stage early warning is triggered corresponding to different inspection or disposal processes. According to the invention, through the whole process optimization of dynamic sampling-layered transmission-federated learning evaluation-multi-stage early warning, efficient, accurate and low-consumption monitoring of the traffic engineering facility safety state is realized, and the contradiction between data privacy protection and evaluation precision is solved at the same time.

The invention relates to the technical field of mobile payment, in particular to a dynamic adjustment method for a mobile payment password-free limit, which comprises the following steps: when a payment terminal initiates a payment request, acquiring a network environment, an equipment unlocking mode, an SIM card state, system integrity and a discrete state of an application environment in real time, and establishing an equipment security state vector; according to the invention, multi-dimensional acquisition is carried out on the network environment, the equipment unlocking mode, the SIM card state, the system integrity and the discrete state of the application environment, and the security state vector is constructed, so that the equipment security can be subjected to structured description before the transaction is initiated, and the security fluctuation characteristics during the operation of the equipment are captured; by means of a security product attenuation value generated by a security state vector and in combination with a highest password-free quota reference value set by a user, a comprehensive equipment security score is output in a nonlinear function form, and quantitative filtering of equipment credibility is realized in a previous stage of quota calculation.

The embodiment of the invention provides a security management method and device, a security chip, electronic equipment and a storage medium. The method is applied to a security chip, the security chip is connected with a management component of the computing device through a first interface arranged on first security processor firmware, a first storage medium is arranged on second security processor firmware of the security chip, and the method comprises the following steps: responding to a data access instruction; and running the first secure processor firmware and the second secure processor firmware, and executing an access operation of the measurement data corresponding to the data access instruction in the first storage medium based on a communication mechanism between the first secure processor firmware and the second secure processor firmware. According to the technical scheme, data communication between the management component and the second security processor firmware is realized, so that the management component can read the measurement data in the first storage medium, and the security state of the computing equipment is monitored and managed.

The invention relates to the technical field of data asset checking, and discloses an intelligent data asset checking system. The system comprises a hierarchical relationship judgment module, a storage state monitoring module, a safety state monitoring module, an asset value calculation module, a hierarchical disposal execution module, a storage strategy optimization module and other auxiliary modules. The hierarchical relation judgment module generates a topological graph, identifies an abnormal path and activates other monitoring modules; the storage and security state monitoring module outputs a health degree evaluation result and a security threat report respectively; the asset value calculation module is combined with the multi-dimensional data to generate a retention or migration decision; and the hierarchical processing execution module optimizes the storage position and the access authority accordingly. The full-process intelligent management of the data assets is realized, and the problems that omissions are easy to occur and a topological structure is difficult to present due to dependence on manual sorting in existing data asset checking, storage and security state monitoring are disjointed with a checking process, and a decision and an actual business demand are disjointed due to single value evaluation dimension are solved.

The invention discloses a vehicle collision early warning method, system and device and a storage medium. The method comprises the steps that first safety state information between a master vehicle and a slave vehicle is acquired through a V2V communication module; performing primary collision risk assessment on the master vehicle and the slave vehicle according to the first safety state information, and performing collision early warning; acquiring second safety state information between the master vehicle and the slave vehicle through a UWB ranging module; calculating a state data deviation based on the first security state information and the second security state information; when the state data deviation exceeds a preset threshold value, secondary collision risk assessment is conducted on the master vehicle and the slave vehicle according to the second safety state information, and collision early warning is conducted. The UWB technology is utilized to overcome the defects of the existing V2V technology in the aspects of positioning precision, data credibility and communication delay, high-precision verification is carried out, and secondary early warning is triggered, so that a vehicle collision safety protection system with master-slave cooperation and function complementation is constructed, and the purpose of early warning is achieved.