154 results about "Security layer" patented technology

The invention provides a micro-grid cooperative scheduling method and device, and relates to the technical field of smart grids, and the method comprises the steps: obtaining historical operation data and real-time operation data of a micro-grid system, and data of an external information system; generating load demand and energy equipment output prediction information based on the historical operation data and the data of the external information system; constructing a layered multi-time-scale decision architecture, and performing decision optimization on each layer of agents by adopting a reinforcement learning algorithm; constructing a plurality of heterogeneous agents, and carrying out cooperative scheduling on the plurality of heterogeneous agents by adopting a centralized training and distributed execution multi-agent reinforcement learning algorithm; inputting the prediction information and the real-time operation data into a decision framework, and outputting a real-time control instruction; and setting a security constraint condition, and realizing optimization of the security constraint in combination with a Lyapunov function, a Lagrange multiplier method, a security layer mechanism and a reinforcement learning algorithm. According to the method provided by the invention, the safe, efficient and reliable operation of the micro-grid in the grid-connected / off-grid mode can be realized.

Systems and methods for securing agent communications in a multi-agent system including deploying an agent to communicate with external servers, instantiating a sidecar security service in communication with the agent and including at least one of a guardrails service, a security layer, an encryption module, and an integrity checker configured to validate resources tools using hash-based verification mechanisms. Communications including messages between the primary and the external servers are intercepted by the sidecar security service, which then performs at least one of filtering the one or more messages by the guardrails service, authenticating one or more server connections by the security layer, encrypting one or more outbound requests by the encryption module, or verifying an integrity of resources and tool definitions by the integrity checker.

The invention discloses a vehicle communication fault source determination method and related equipment, and relates to the technical field of vehicle communication, the method comprises the following steps: obtaining communication operation information of a plurality of processing levels in a vehicle communication system, the plurality of processing levels comprising a hardware layer, a middle layer, a security layer and a network layer; based on a preset log format, recording the communication operation information, and generating an encrypted log; and performing fault root cause analysis on the encrypted log through a preset fault tree model to obtain a target fault source. Through multi-level log acquisition and fault tree analysis, in combination with a structured format and encrypted storage, vehicle communication fault diagnosis with accurate and efficient fault positioning, data traceability, safety and credibility can be realized.

The invention provides a fusion type secure storage system, electronic equipment, a data management method and a computer readable storage medium. The system comprises a hardware security layer, an encryption processing layer, a verification error correction layer, a data stream processing layer and an intelligent management layer which are in communication connection, the hardware security layer provides a physical trusted root for the system and executes a security policy; the encryption processing layer is used for carrying out encryption processing on data based on the security service provided by the physical trusted root; the verification and error correction layer is used for carrying out integrity verification and self-adaptive error correction coding on the encrypted data; the data stream processing layer is used for executing a near data calculation task on the data subjected to verification and error correction; and the intelligent management layer collects real-time state data from the hardware security layer, the encryption processing layer, the check error correction layer and the data stream processing layer, and performs dynamic strategy configuration and global optimization decision, thereby improving the active calculation, dynamic adaptation and intelligent optimization capabilities of the system.

The invention provides a large language model safety protection defense method and device based on dynamic regulation and control, and belongs to the field of artificial intelligence safety protection. The large language model security protection defense method comprises the following steps: constructing a non-security data set and a security data set jail break prompt data set, calculating a gradient average value of parameters of each layer of a large language model during back propagation of various data sets, calculating cosine similarity among gradients, determining a non-security layer, namely a layer most sensitive to non-security content, and performing security protection defense on the non-security layer. Therefore, the subsequent regulation and control are more accurate and effective; in the aspect of dynamic regulation and control of a specified non-security layer, a joint loss function is established to optimize and train a security offset vector, and the security offset vector is applied to a hidden state of the non-security layer in a big language model reasoning process to carry out intervention, so that output of a big language model is dynamically regulated and controlled; therefore, the robustness of the large language model is improved.

The invention discloses an intelligent RAG enhanced large model auxiliary writing system, and relates to the technical field of artificial intelligence auxiliary writing. In order to overcome the defects of an existing writing auxiliary tool, the adopted scheme comprises an interface and user layer for receiving a writing demand and redisplaying a generation result; the service layer is used for deploying three types of intelligent agents including writing, interactive writing enhancement and checking; the platform layer is used for carrying out industry adaptation analysis, mixed retrieval and RAG enhancement on writing demands and then sending the writing demands to the large model layer; three intelligent agents of writing, interactive writing enhancement and checking are called in sequence based on the output of the large model layer, and then a text is redisplayed to the interface and user layer after fact accuracy verification is completed through a tense knowledge graph; the data layer is used for providing a multi-type data storage system; the large model layer outputs a paragraph-level text and a reference index based on a writing large model, the paragraph-level text is returned to the platform layer, and reference index information is fed back to the interpretability and security layer for tracing; and the infrastructure layer is used for providing bottom layer resource support for each layer.

The invention relates to a highway curve construction area intrusion early warning system and method, and belongs to the technical field of highway early warning. The system is divided into a sensing layer, a decision-making layer, an execution layer and a guarantee layer. The sensing layer is composed of a multi-level thundersight all-in-one machine; the decision-making layer is edge computing nodes deployed in a distributed manner; and the execution layer comprises an intelligent roadside warning device and wearable terminal equipment. In the sensing layer, all sensing data monitored by the multi-level thundersight all-in-one machine is transmitted to an edge computing node through a time sensitive switch, the edge computing node carries out space-time alignment on a point cloud signal monitored by the thundersight all-in-one machine and a visual recognition result through a multi-source data fusion algorithm, and the data after space-time alignment is input into a CTRA model, so that the CTRA model is constructed. And the CTRA model judges the intrusion risk of the vehicle according to the received data and outputs a corresponding decision instruction data packet, and the decision instruction data packet is transmitted to the execution layer. And the execution layer executes corresponding sound-light-vibration multi-dimensional early warning according to the corresponding instruction in the decision instruction data packet.

The invention discloses a supply chain order business automatic processing system and a method thereof. The system comprises a dynamic intelligent center, an elastic process engine, a green loop network and a trusted security layer, the dynamic intelligent center dynamically optimizes decisions through federated learning and generative AI, and the elastic process engine realizes flexible recombination of processes based on micro-service and a low-code platform. The green circulation network utilizes a block chain to track carbon footprints and manage reverse resources, and the credible security layer adopts quantum encryption and dynamic authority to guarantee data credibility. The corresponding method comprises the steps of combining a multi-party data training model and generating a multi-scheme, performing a micro-service splitting and low-code configuration process, driving intelligent contract transaction by a carbon label, and performing quantum encryption evidence storage and anomaly detection. Through the edge-cloud collaborative architecture, the scheme synchronously improves the efficiency, flexibility and sustainability, solves the problems of insufficient intelligence, framework stiffness and security defects in the prior art, and is suitable for complex scenes such as e-commerce and manufacturing.

The invention discloses a security hierarchy penetration data management system and method of a multi-model collaborative engine, relates to the field of data management, and is used for solving the problems that provincial data is difficult to efficiently directly reach a base layer and base layer data cannot be fully reflowed and added due to a hierarchy barrier existing in a traditional data management mode. The system comprises a large model layer, a basic service layer, a service governance layer and an application layer. According to the method, a hierarchical barrier is broken, provincial-level data can directly reach a base layer, safe and ordered flow of the data is ensured through authority control and access queue control of the MCP gateway, and meanwhile, a data asset pool shared by the whole province is formed through backflow and increment of the base layer data. The large model is enabled, through multi-model pipelined cooperation and cross-system data association, the advantages of the large model in the aspects of data cleaning, semantic understanding, early warning and prediction and the like are fully played, and the intelligent level of government affair data processing is improved.

The invention provides a big data integration and distribution unit component of a hierarchical architecture and a use method, relates to the technical field of data integration and processing, and solves the problems of real-time integration, unified processing and safe distribution of multi-source heterogeneous data. The device adopts a five-layer modular architecture; a data access layer supports multi-source data access and is buffered through Kafka; the cleaning conversion layer performs data cleaning and standardization by using a FlinkSQL, an ETL engine and a rule engine; the intelligent distribution layer judges a data distribution path in combination with a rule engine and a machine learning model; the storage calculation layer adopts a cold and hot separation storage strategy and supports parallel operation of Spark batch processing and Flink stream processing; and the service and security layer provides an interface through an API gateway, and guarantees data security in combination with AES-256 encryption and RBAC access control. Besides, dynamic resource scheduling is realized through Kubernetes, cross-domain model cooperative training is supported by utilizing a federated learning technology, the intelligent shunting decision-making capability is improved, various industrial protocols such as MQTT and Modbus are compatible, and VXLAN tunnel transmission is supported.

The invention discloses an engineering vehicle driver behavior analysis system based on federal learning. The system comprises a multi-source sensing layer which forms vehicle-road-person collaborative all-weather scenarized data input; the edge calculation layer is used for capturing a complex space relationship of a driving scene, embedding a lightweight cross-modal attention module, calculating an attention weight, and processing long-sequence driving operation data by adopting a Mamba state space model to capture a long-term dependency relationship of a driver state; the federated learning layer adopts a pFedMe algorithm to realize a driver customized model, during local training, the model learns local data distribution characteristics through a Moreau Envelopes regularization item, the cloud aggregates distribution of adaptive local data of each driver, models a federated learning process as a meta-learning problem, and performs training updating; a privacy and security layer; and differential privacy dynamic adjustment, Paillier improved homomorphic encryption and a Hyperledger Fabric block chain are adopted to prevent a log from being tampered.

The invention provides a software and hardware integrated intelligent terminal power transaction system and method, relates to the technical field of power market transaction, and solves the technical problems of data potential safety hazards and insufficient real-time performance caused by dependence on an external platform in a power transaction process in the prior art. The system specifically comprises a hardware architecture and a software function module, the hardware architecture comprises a processor, a redundant power supply, a storage device, a network interface, a security encryption chip and a display interface; the software function module comprises a core function layer, an interface layer and a security layer; wherein the core function layer is used for being responsible for processing and controlling the whole flow of power transaction; the interface layer is used for carrying out standardized and ordered external data interaction; and the security layer is used for guaranteeing the security of the terminal from multiple dimensions of communication, transaction, data and operation and maintenance. The method is used for electricity market transaction.

The invention relates to the technical field of intelligent robot control, in particular to a small robot dynamic balance control system based on DDPG, which comprises a sensor and a preprocessing module, provides accurate and reliable state data through denoising and standardization processing, and enhances the accuracy of subsequent processing; the ESO observer module estimates the system state and the total disturbance in real time, and the adaptive capacity and the anti-interference performance to the complex environment are improved; the information fusion and time sequence alignment module ensures information synchronization and accuracy through fusion processing and multi-dimensional state vector construction, meanwhile, the timeliness of a control decision is ensured, and the overall control effect is improved; the DDPG strategy network and the security layer module are combined with strategy optimization and multi-layer security constraints, continuous and safe control actions are output, and the stability and security of control are improved; and the actuator interface module realizes control instruction transmission, forms closed-loop feedback, adjusts a control strategy in real time, and improves the dynamic balance capability and the overall stability of the system.

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

The invention discloses a vehicle-mounted system safety detection and risk assessment system, which belongs to the technical field of vehicle-mounted network safety, and comprises a vehicle-mounted terminal environment sensing module used for collecting multi-level environment information of a vehicle-mounted system, including system layer information, network layer information and safety layer information; the vehicle-mounted configuration file and communication white list detection module is connected to the vehicle-mounted terminal environment sensing module and is used for establishing and maintaining a safety white list library according to the collected system information, comparing the current configuration file, the dynamic library, the port and the certificate state of the system with the safety white list library through periodic scanning, and sending the comparison result to the vehicle-mounted terminal environment sensing module; detecting configuration abnormity and file tampering events; a vehicle-mounted process and control task analysis module; a communication abnormity detection and code identification module; and a safety evaluation and risk feedback module. According to the invention, all-around monitoring and intelligent analysis of vehicle-mounted system configuration, process behaviors and network communication can be realized, and hidden backdoors, abnormal processes and malicious communication can be effectively identified.

The invention discloses a multi-AUV safe path planning method based on deep reinforcement learning. According to the method, a deep reinforcement learning algorithm model based on an MATD3 method is adopted, a policy network and a value network are updated by adopting security constraints, the security of policy learning is improved, the expected reward revenue is maximized under the condition that the expected security cost constraints are met, a frequent minimum and maximum optimization process is avoided by adopting first-order penalty optimization, and the security of policy learning is improved. Meanwhile, safety correction based on a safety layer is added in the training process to guarantee safety in the early stage of training, and exploratory and safety balance is brought to strategy optimization of reinforcement learning through safety constraint and safety correction. According to the multi-AUV path planning method, the time cooperation constraint and the space cooperation constraint of multi-AUV path planning are comprehensively considered, the centralized training and decentralized decision-making architecture is applied to multi-AUV path planning, the path planning method capable of ensuring cooperation safety is provided for a multi-AUV system, and the safety and the reliability of path planning are improved.

A quadruple port hiding method and device based on a zero trust architecture belong to the field of computer network security and comprise a first knock operation and a terminal trust evaluation method based on a space-time matrix fusion multi-factor model, a multi-element identity authentication based on trust, a tunnel port knock, and a service port knock.The quadruple port hiding zero trust access control scheme is adopted to knock the zero trust security management platform, the identity authentication port, the VPN tunnel port in the SDP gateway, and the service port, so that the comprehensive protection enhancement of user access and service is realized.The quadruple port hiding technology increases an additional security layer, so that it is difficult for an attacker to easily find an effective attack entry point;meanwhile, the identity authentication mechanism based on trust can realize more refined access control and can adapt to a complex network environment, so that the security vulnerabilities existing in the traditional SPA mechanism are avoided.

The invention discloses a secure transmission method and device of multimedia data, equipment, a medium and a product. The method comprises the following steps: acquiring multimedia stream data to be transmitted and a supplier ID; encrypting the multimedia stream data to be transmitted based on the supplier ID to obtain encrypted information; and packaging the supplier ID and the encrypted information according to an improved supplier specific format to form a to-be-transmitted data packet and transmit the to-be-transmitted data packet, the improved supplier specific format comprising an encrypted payload structure. An encryption effective load structure is added to an improved supplier specific format, an encryption key is dynamically generated by using a supplier ID, and to-be-transmitted stream data is encrypted and packaged into an encrypted to-be-transmitted data packet. According to the method, the security of the data stream is enhanced, encryption of stream data can be realized without an additional security layer, different specific formats of the improved suppliers can be configured for different suppliers, the requirements of various applications are met, and market innovation and competitive advantages are promoted at the same time.

Systems and methods for securing agent communications in a multi-agent system including deploying an agent to communicate with external servers, instantiating a sidecar security service in communication with the agent and including at least one of a guardrails service, a security layer, an encryption module, and an integrity checker configured to validate resources tools using hash-based verification mechanisms. Communications including messages between the primary and the external servers are intercepted by the sidecar security service, which then performs at least one of filtering the one or more messages by the guardrails service, authenticating one or more server connections by the security layer, encrypting one or more outbound requests by the encryption module, or verifying an integrity of resources and tool definitions by the integrity checker.

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

The invention relates to the field of path planning, and discloses an unmanned surface vehicle track planning method and device and a medium, and the method comprises the steps: obtaining the real-time dynamic water area environment information of an unmanned surface vehicle; constructing a decision model of unmanned surface vessel track planning, and adopting an improved deep reinforcement learning SAC method based on strategy divergence to train and iteratively solve the decision model to obtain an optimal approximation strategy, namely a trained decision model; and inputting the real-time dynamic water area environment information into a trained decision model to obtain an optimal execution action of the unmanned surface vessel, and completing route planning. According to the method, a constraint perception adaptive entropy adjustment mechanism and a security layer verification module are innovatively introduced, so that the algorithm actively perceives and avoids risks in each stage of training and execution, the multi-target balance problem is successfully solved, and the USV autonomous operation capability and the navigation safety level are remarkably improved.

The invention provides a multi-virtual machine isolation operation system based on security level automatic scheduling, and relates to the technical field of cloud computing and virtualization. According to the system, an intelligent security level evaluation module is combined with multi-dimensional analysis to generate a task security level, a security-layered virtual machine resource pool realizes hierarchical cluster management and elastic scaling, an intelligent scheduling engine realizes task allocation based on security level matching and resource optimization, and a cross-level data exchange control module realizes fine-grained data management and control. The system solves the problems that an existing virtual machine management system is insufficient in security isolation, low in manual scheduling efficiency, poor in dynamic adaptability and weak in cross-domain data management and control, deep binding of the security level and resource allocation is achieved, and the resource utilization rate and the system robustness are improved. Performing subject term cloud computing; a virtualization technology; a security level; isolating the virtual machine; and automatic scheduling.

The application discloses a kind of multi-level quantitative evaluation methods for electronic product information clearing, verification and traceable credible closed-loop system, comprising S100, evaluation framework establishment and test environment preparation step: S110, define evaluation model, the evaluation model includes clearing effect layer (L1), verification credible layer (L2), trace and authentication layer (L3), system behavior and security layer (L4) and performance and efficiency layer (L5).The application has the advantages that: from qualitative to quantitative: a large number of quantitative indicators such as KL divergence, bit recovery rate, throughput are introduced, and the evaluation results are objective, accurate and comparable.The method carries out deep security testing: not only test function, but also take the system itself as attack target, carry out penetration testing and process behavior monitoring, can find deeply hidden design defects and security vulnerabilities, which cannot be achieved by traditional function testing.At the same time, the method can guide technology development, and provide decision basis for procurement and supervision;And high automation and repeatability.

A method for securely transmitting time-critical data within a communication system including local networks in which data are transmitted via switching, at least one network superimposed with respect to the local networks, in which data are transmitted via routing, and a gateway system for connecting the communication system to an unsecured external network, wherein network layer communication via the superimposed network is authorized only between authenticated system components, switches authenticate connected terminal devices and assign these to a physical or logical local network in accordance with a respective terminal device identity, security layer communication is authorized within the local networks implicitly based on an assignment of respective terminal devices to the same local network, communication at OSI layer 3-7 between terminal devices of different local networks or with terminal devices in the unsecured external network is authorized via zero trust proxies that are each assigned to a local network.

A casting control method and apparatus are provided. The casting control method and apparatus are applied to the field of video processing technologies. The method is applied to a first electronic device. The first electronic device includes a GPU and an HWC. When the first electronic device is in a casting state, the to-be-synthesized layer can be separately sent to the GPU and the HWC if the video security layer is not included. The first electronic device synthesizes the to-be-synthesized layer in parallel by using the GPU and the HWC.

The application provides a soft and hard cooperative security AI NAS storage and calculation system and an access authentication method, and belongs to the technical field of network storage. The system comprises a hardware security layer, a lobster security core module, a compulsory authentication gateway, an encrypted storage engine, an intelligent access control module and a security audit and monitoring module. The hardware security layer comprises a lobster security chip and a hardware root of trust module. The lobster security chip is an independent security processor, and is internally provided with a true random number generator, an encryption acceleration engine and a security storage area. The hardware root of trust module is used for system startup verification and root key hardware protection. Through the soft and hard cooperative architecture and the compulsory authentication mechanism, the application realizes a complete trust chain from the hardware root of trust to the application layer, can effectively prevent ransomware attacks and data leakage risks, and improves data operation efficiency.

The invention discloses a data encryption method and device, equipment and a storage medium, and relates to the technical field of information security, and the method comprises the steps: receiving a data encryption request which is sent by a business application and carries a tenant identifier, an application identifier and to-be-encrypted data; querying an application key ciphertext corresponding to the application identifier and a tenant key ciphertext corresponding to the tenant identifier from a tenant security layer, and obtaining a platform master key from a platform security layer; decrypting the target tenant key ciphertext by using the platform master key in the tenant security layer to obtain a tenant key plaintext, and decrypting the application key ciphertext by using the tenant key plaintext to obtain an application key plaintext; and sending the application key plaintext and the to-be-encrypted data to a virtual cipher machine allocated to the current tenant in advance, encrypting the to-be-encrypted data based on the application key plaintext to obtain a data ciphertext, and sending the data ciphertext to the service application. According to the invention, the security of the data encryption process can be improved, and data leakage is avoided.

The invention provides a perception adaptive video stream code rate decision-making method and system based on a neural symbol reinforcement learning buffer area, and belongs to the technical field of computer network and multimedia transmission. According to the method, a neural symbol reinforcement learning agent is constructed, a comprehensive state vector is generated by collecting a playing state, video content information and user preference, and double decisions of code rate selection and buffer area adjustment are jointly output; security rules are formalized in a first-order logic mode, security exploration is achieved through a security monitor and a security layer strategy, and illegal risks such as underflow of a buffer area are avoided; the bandwidth prediction precision is improved by adopting HTTP / 3 stable connection sampling and a hybrid prediction model; and designing a multi-target reward function to balance user experience quality and buffer occupation optimization. According to the method, high-video-quality, low-lagging and low-delay transmission can be stably realized in a low-speed to 5G high-speed network, and unnecessary buffer accumulation can be remarkably reduced on the premise of ensuring smooth playing, so that end-to-end delay is reduced.

The invention relates to the technical field of machining process control, in particular to a plate connection parameter dynamic adjustment method based on multi-level rule judgment, which comprises the following steps: constructing a three-level rule judgment system including a material safety layer, a quality guarantee layer and a process optimization layer; taking a material characteristic set obtained based on finite element numerical simulation as process parameter input, and sequentially executing rule judgment according to the hierarchical priority sequence; material stress field distribution and thermal deformation data adjustment safety threshold values are calculated in real time; calling a multi-level rule tree corresponding to the material type, performing iterative operation from a leaf node to a root node of the multi-level rule tree to obtain final process parameters of the material, and performing systematic verification; and generating an equipment control instruction set from the verified process parameters according to a standard format, and outputting the equipment control instruction set to an execution end. According to the method, the processing safety, the quality stability and the process optimization effect can be remarkably improved, meanwhile, the equipment debugging cost is reduced, and the reliability and compatibility of process parameters are enhanced.

An example operation may include one or more of receiving blockchain specification information, generating one or more security configuration files for a blockchain based on the blockchain specification information, and launching the blockchain on a host platform, and hooking into the host platform via one or more modules which configure security settings of the blockchain based on the one or more security configuration files.