809 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.

A system and methodology for automated security assessment of microservices includes a microservice composition model, data gathering, security assessment, and labeling components. It treats microservices as separate projects, collecting source code, dependencies, and runtime information. The security assessment employs tools to analyze code, track vulnerabilities, and identify risks. Predefined rules categorize microservices and assign security state labels. A hidden Markov model predicts security states based on historical data, enabling proactive security management and risk mitigation.

The invention discloses a substation network security defense system based on artificial intelligence. The system comprises a data collection module for collecting transformer substation network data; the anomaly detection module is used for identifying an abnormal mode and an intrusion behavior; the threat intelligence analysis module is used for identifying potential threat and vulnerability information; the intelligent security monitoring and response module is used for evaluating the network security state; the malicious code detection module is used for detecting, analyzing and isolating malicious software; the intelligent security prediction module is used for predicting a network security event and carrying out early warning prompt; the self-adaptive security policy module is used for automatically adjusting or updating an optimal security policy; the system updating and maintaining module is used for updating and maintaining system modules and functions; the user interface and alarm module is used for providing safety state display and alarm for a user; the data backup and recovery module is used for backing up and recovering key data; and a compliance auditing module which makes operation and configuration accord with security standards. According to the invention, hierarchical, intelligent and active protection of the transformer substation network is realized.

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.

Systems and techniques are provided for establishing a connection. For instance, a process may include receiving, by a first root of trust (C-ROT) of a first chiplet of a plurality of chiplets from a second C-RoT of a second chiplet, a second certificate along with security state information and debug information for the second chiplet; authenticating a security state and a debug state of the second chiplet based on the security state information and the debug information; authenticating the second certificate; and establishing a security boundary with the second chiplet.

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 a linkage early warning method based on security situation assessment and application thereof. The linkage early warning method comprises the following steps: data preprocessing and feature extraction; an abnormal evaluation model and a normal evaluation model are constructed, and training and parameter adjustment are carried out; evaluating the data acquired in real time by using a safety evaluation function, judging the current safety state of the hydraulic power plant, and outputting a safety parameter; constructing a decision function, and determining whether the current state is abnormal or not based on the safety parameters and environmental factors EnvFactors; dynamically selecting and determining to select an abnormal evaluation model and a normal evaluation model for real-time evaluation, and judging whether the current state needs early warning or not; when early warning is needed, an emergency command system and early warning information are linked to carry out early warning and emergency response, and possible safety risks of the hydraulic power plant are prompted. According to the invention, by constructing the security evaluation function and the decision function and combining the neural network model, the problem that the existing system lacks enough flexibility and adaptability and cannot effectively cope with variable network security threats is solved.

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 relates to the technical field of reservoir dam safety risk research, in particular to a small and medium-sized reservoir dam safety evaluation method, a computer readable storage medium and electronic equipment. The small and medium-sized reservoir dam safety evaluation method disclosed by the invention specifically comprises the steps of firstly obtaining dynamic indexes for dam safety evaluation based on an index classification function, then constructing an evaluation system based on the obtained dynamic indexes, then carrying out weight calculation on the dynamic indexes by adopting an improved analytic hierarchy process, and finally, carrying out dam safety evaluation. The dam safety is evaluated by adopting an improved fuzzy analysis method in combination with an evaluation system and the weight of a dynamic index, the dam safety real-time state can be accurately evaluated, the evaluated dam safety state is dynamically updated in real time, real-time information is provided for the safety management of the dam in the later extreme climate and environment, and the safety of the dam is improved. And a manager can make a timely and accurate decision when the dam encounters a risk.

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 relates to a park equipment operation monitoring method and system, computer equipment and a storage medium, and the method comprises the steps: carrying out the real-time collection of operation parameters of energy nodes in a park, carrying out the denoising and standardization processing of the operation parameters through signal processing, and obtaining standard parameter data; obtaining a park task list, monitoring the standard parameter data in real time based on a preset operation rule, and generating a state evaluation report of the power distribution system; key operation data in the ground source heat pump system are collected, evaluation is carried out through a trend analysis algorithm in combination with historical operation data, and an equipment operation prediction report is generated; acquiring real-time environment monitoring data and video monitoring data of a preset important area, performing environment state evaluation and safety state evaluation on the park, and generating an environment safety monitoring report; and constructing a virtual three-dimensional model of the park, and integrating the monitoring parameters to the virtual three-dimensional model. The method and the device have the effect of improving the monitoring efficiency of the equipment in the park.

The invention discloses a power meter reading concentrator remote upgrading system and method based on a 4G communication module. The system comprises a power meter reading concentrator, a remote server, a management terminal and a security authentication module. The concentrator is internally provided with a 4G communication module and establishes secure communication with a remote server through a 4G network, so that remote upgrade of firmware or software is realized. The system adopts block transmission and breakpoint resume technologies, and it is ensured that the upgrade package can still be efficiently and completely transmitted under the condition that the network is unstable. In the upgrading process, SSL / TLS encryption is adopted for data transmission, and safety is guaranteed; meanwhile, the system has self-checking and rollback functions, and it is ensured that the system automatically recovers to a safe state when upgrading fails. According to the invention, the upgrading and maintenance efficiency of the electric power meter reading system is remarkably improved, the operation and maintenance cost is reduced, and the reliability and safety of the system are improved.

Systems, apparatus, articles of manufacture, and methods are disclosed for template generation to enforce desired states on cloud accounts. An example apparatus disclosed herein includes programmable circuitry to access a privilege from a cloud account, the privilege associated with a resource to be deployed based on a template, validate the privilege relative to template privileges specified in the template, secure the resource before deployment of the resource by imputing a privilege access condition to the resource based on the privilege satisfying at least one of the template privileges, and deploy the resource based on the template in a secure state, the secure state corresponding to the privilege access condition.

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 relates to the technical field of information security, in particular to an information security cloud computing platform based on an intelligent computing center, which comprises a user identity and access control module, a self-adaptive threat detection module, a data protection and backup module, a virtualization and resource management module, an edge computing collaborative security module and a security event management module, the user identity and access control module performs identity verification and management; the self-adaptive threat detection module automatically analyzes and identifies novel security threats; the data protection and backup module encrypts the stored and transmitted data; the virtualization and resource management module manages and monitors the security state of the virtual machine; the edge computing collaborative security module deploys a security agent at an edge node; and the security event management module records security events of the platform. According to the method, the accuracy and real-time performance of threat detection and response are improved, and efficient and safe operation of the platform is ensured.

This application discloses a security assessment method and apparatus, an electronic device, and a readable storage medium. The security assessment method is applied to an electronic device that supports a trusted execution environment TEE and a rich execution environment REE, where the method includes: in a case that a security information query request for querying a security status of the electronic device that is sent by a server is received by the REE side, obtaining REE security status information and sending the security information query request and the REE security status information to the TEE side; obtaining target security information from the TEE side and generating comprehensive security information based on the REE security status information and the target security information, where the target security information includes TEE security status information; and sending the comprehensive security information to the server.

The invention discloses an Internet of Things service management system based on regional digital economy, and relates to the technical field of data processing. The Internet of Things service management system based on regional digital economy comprises a data minimization and anonymization module, an end-to-end encryption module, an access control and identity authentication module, a data security and auditing module and a security management and response module, and the data minimization and anonymization module is used for collecting personal sensitive information data; the end-to-end encryption module is used for encrypting a personal sensitive information data transmission process; the access control and identity authentication module is used for multi-factor authentication; the data security and audit module is used for protecting personal sensitive information data; and the security management and corresponding module is used for dynamically adjusting security policies and measures according to the privacy security state evaluation value. The problem that in the prior art, as the number of devices increases, more and more personal data are collected, and once sensitive data are integrated and analyzed, personal privacy may be exposed is solved.