119 results about "Adaptive security" patented technology

The invention discloses a real-time multi-dimensional sensitivity evaluation and self-adaptive safety prevention and control method and system for natural resource geographic information. The method comprises the following steps: acquiring real-time natural resource geographic information data; obtaining a preset behavior graph model; updating a preset behavior graph model according to the real-time natural resource geographic information data so as to obtain an updated behavior graph model; acquiring an updated node risk vector according to the updated behavior graph model; obtaining a trained Bayesian risk prediction model; inputting the updated node risk vector into a trained Bayesian risk prediction model so as to obtain a real-time abnormal behavior identification result; and generating a personalized prevention and control strategy scheme according to the real-time abnormal behavior recognition result. According to the method, intelligent identification, dynamic evaluation and active protection of natural resource geographic information in a full life cycle are realized by constructing a multi-dimensional sensitivity quantitative model, a dynamic risk perception mechanism based on a graph structure and a safety prevention and control strategy capable of being updated in real time.

The invention belongs to the technical field of intelligent electric power internet of things, and particularly relates to an unmanned aerial vehicle heterogeneous terminal self-adaptive security access method for electric power edge computing, which comprises the following specific steps: terminal registration and credible anchoring: binding a hardware-level identity, collecting a multi-mode fingerprint and constructing a security behavior portrait; self-adaptive access authentication is carried out; dynamic behavior monitoring and baseline adjustment: establishing an identity authentication and management system, synchronously carrying out multi-dimensional real-time monitoring, carrying out linkage treatment on abnormal behaviors, and adopting a baseline evolution mechanism to avoid misjudgment; the multi-dimensional real-time monitoring comprises terminal service trend monitoring and flow situation analysis; and performing safe closed loop and cooperative response. According to the invention, unified risk detection of the unmanned aerial vehicle can be realized, real-time monitoring of vulnerabilities, access authority and operation states of the unmanned aerial vehicle is carried out, a dynamic behavior monitoring model is constructed in combination with unmanned aerial vehicle terminal information, business data, environment data and the like, and real-time monitoring and early warning of the unmanned aerial vehicle terminal are realized.

The present disclosure provides a method for secure message encryption and decryption using witness encryption. The method includes generating a master public key and a master secret key, generating common reference strings for a non-interactive zero-knowledge (NIZK) proof system and a commitment scheme, creating commitments using random values, and setting the master public and secret keys. A function key is generated by creating a dummy function tag and a NIZK proof. Message encryption involves generating a dummy input tag and creating a witness encryption ciphertext. The encrypted output includes attributes, the dummy input tag, and the witness encryption ciphertext. Decryption is performed using the function key and a witness decryption algorithm. The method enables secure message transmission with confidentiality and integrity throughout the encryption and decryption phases.

The invention discloses a self-adaptive security protection method for an internet of things terminal, and the method achieves the joint perception and collaborative response of security threats of a physical side and a network side through the construction of a lightweight cross-domain feature perception and resource dynamic adaptation mechanism. According to the method, the physical service criticality and the network attack threat are quantitatively associated, and the optimal security policy is dynamically selected according to the real-time computing power state of the terminal, so that the accurate balance between the protection strength and the service continuity is realized under limited resources. By introducing a resource-aware dynamic scheduling mechanism, the Internet of Things terminal can intelligently degrade or switch a protection strategy in a high-load or high-threat scene, and service interruption caused by resource exhaustion is avoided. Finally, the identification and defense capabilities for information-physical cross-domain hidden attacks are remarkably improved, stable operation and continuous protection of the terminal under harsh resource constraints are ensured, and finally, dual guarantee of security efficiency and service reliability is realized.

The invention provides a zero-trust-based dynamic data secure transmission and processing channel construction device and method, and the method comprises the steps: S1, collecting to-be-transmitted data, and classifying the data to obtain a data classification result; s2, based on the data classification result, the user identity information and the environmental risk information, a dynamic security policy is generated, and the dynamic security policy comprises an encryption algorithm selection rule, a trust evaluation threshold and a data operation authority policy; according to the invention, the fine-grained security policy is generated and continuously adjusted by dynamically sensing the data sensitivity and the real-time trust state, so that the full-link self-adaptive security protection from transmission to processing is realized; according to the method, the security multi-party calculation is seamlessly integrated in a high-sensitivity scene, so that the end-to-end security and privacy protection level of data in a cross-domain and multi-participant environment are remarkably improved while the data mobility is guaranteed, and the problem that a traditional static security mechanism is difficult to adapt to dynamic risks is effectively solved.

The invention discloses a large model adaptive security detection method and system based on four-order linkage, and the method achieves the security detection of the output content of a large model through four-stage collaborative linkage: in the context consistency reasoning stage, calculating the semantic consistency score of a generated text, a multi-round dialogue history, a user prompt word and an external knowledge base; marking a potential risk; in the causal chain risk detection stage, modeling multiple rounds of dialogues into a causal graph, calculating a risk path probability, matching an attack pattern library, and marking high risks; in the dynamic game optimization stage, a game space of a detector and an attacker is constructed, an optimal detection threshold value is solved, and parameters of each stage are linked and updated; in the cycle state switching stage, switching is carried out between a low-power-consumption monitoring state and a dynamic updating state according to system performance and a risk situation, and a risk level is output by integrating results of the four stages. According to the method, the problems of low hidden attack detection rate, high false alarm, risk non-traceability and resource waste in the prior art are solved, and self-adaption, low false alarm, traceability, high efficiency and energy conservation are realized.

The invention discloses an NFC-based payment communication method and an application thereof in a payment transaction terminal, the scheme can be used for transaction interaction of the payment transaction terminal in a card reader mode and an NFC TAG mode, when the terminal is in the NFC TAG mode, different guides are provided by identifying an operating system of payment terminal equipment serving as card reading equipment, and the payment terminal equipment is more convenient to use. The convenience and intelligence of the application payment means are improved; according to the scheme, in combination with the characteristics of equipment operating system identification and equipment moving, corresponding voice or UI prompts are given when transaction is not completed for a long time and equipment which identifies an IOS system is subjected to transaction, in order to prevent a single order from being paid by multiple pieces of equipment, emptying is carried out after it is confirmed that the content of the NFC tag is completely read, and the payment efficiency is improved. And the transaction reliability and convenience are improved. And when the terminal is in the card reader mode, whether the transaction card is an entity card is distinguished according to the card searching instruction, and the transaction result is returned to the application layer, so that a self-adaptive security policy is provided.

The invention relates to the field of data security, in particular to a network security intelligent detection method based on big data, and the method comprises the steps: collecting network flow data, a terminal system call sequence and a user operation behavior log, and carrying out the data fusion processing to generate a unified behavior event flow; selecting a key behavior event based on an information entropy threshold value, performing time alignment through a dynamic time warping algorithm, and constructing a behavior gene map containing a communication association gene, an operation sequence gene and a behavior time sequence gene; a dynamic behavior baseline model is established by using unsupervised learning, and gene mutation detection and alarm are realized by calculating the deviation degree of each gene dimension; the detection performance is evaluated based on the false alarm rate, model parameters are optimized through a negative feedback mechanism, and acknowledged attack features are stored in a sharable threat gene feature library through a positive feedback mechanism. According to the method, the detection accuracy is continuously improved through a closed-loop learning mechanism, and a self-adaptive safety protection system with self-optimization capability is constructed.

A computer system and method for managing device trust during digital interactions. The method comprises capturing device data, including static and dynamic parameters, from a device upon user login to a digital platform. Static parameters are analyzed during the initial login to establish a static trust score, while dynamic parameters are analyzed across sessions to establish a dynamic trust score, which is incrementally updated based on subsequent data. The static and dynamic trust scores are combined to generate a combined trust score, and the device is assigned to one of multiple risk clusters. Based on the assigned cluster, adaptive security protocols are triggered. Assignment to a moderate-risk cluster initiates a step-up authentication process, and failure of the process results in assignment to a high-risk cluster, restricting access to the platform.

The invention relates to the technical field of zero trust, and particularly discloses a zero trust security policy intelligent generation method and system for an autonomous AI agent. According to the scheme, proxy behavior data is analyzed through a behavior intention perception module, a task intention of the proxy behavior data is reconstructed, security risks are quantified in real time by a dynamic risk assessment module based on a multi-factor fusion model, a policy generation engine adaptively generates a fine-grained access control policy according to a risk state, and closed-loop optimization is realized through a policy execution and verification loop. According to the method, real-time and self-adaptive security management and control of autonomous AI agency behaviors can be realized, and the perception and defense capability of unknown threats is improved.

The application discloses a kind of anti-network attack's multi-vehicle safety platoon control method and system, the method first establishes multi-vehicle queue dynamics model;Second, design fuzzy state observer to estimate vehicle state and unknown nonlinear dynamics;Then, introduce funnel function to build time-varying performance boundary, and the double constraints of vehicle anti-collision and keep communication are converted into funnel constraints of spacing tracking error;Then, based on backstepping method and funnel performance error, design virtual controller and adaptive law, and obtain adaptive safety controller to obtain control input;Finally, through Lyapunov stability analysis, the tolerance threshold condition that system can still maintain final consistent bounded stable after suffering replay attack is quantitatively obtained.The application simplifies design through funnel control, avoids complex barrier lyapunov function, and for the first time clearly provides quantified anti-interference ability to replay attack, enhances the network security and practicality of multi-vehicle queue system.

The invention relates to the technical field of industrial heat treatment equipment control, in particular to a heat treatment furnace safety control system based on a cloud platform. The multi-dimensional state sensing module is used for collecting real-time physical field data of an industrial controlled object; the signal orthogonal decomposition module is used for decoupling the original state data set into a low-frequency control signal flow and a high-frequency characteristic signal flow, and transmitting the high-frequency characteristic signal flow to a remote computing platform; the state reconstruction module is used for resolving a theoretical state value at the current moment and constructing a virtual sensor observation state; the dynamic envelope generation module is used for calculating a residual error between a theoretical state value and real-time physical field data and generating a dynamic security envelope threshold value and a confidence coefficient attenuation coefficient; and the self-adaptive safety judgment module is used for generating a final safety execution threshold value and executing safety interlocking control on the industrial controlled object. According to the method, the sensitivity of capturing the abnormal working condition in the heat treatment process is improved, and the problem that the static threshold value easily generates false alarm or missing alarm under the complex variable working condition is solved.

The application discloses a short public parameter identity-based proxy re-encryption method based on an LWE problem, a trapdoor matrix, namely a short base on a lattice, is generated through a more simple and efficient trapdoor generation algorithm, the trapdoor matrix is taken as a master secret key MSK, an identity sequence with an l-bit length is divided into l' = l / β blocks through a block technology, the number of public parameter selection is reduced, the size of the master secret key and the public parameter is reduced, the public parameter calculation complexity is reduced, the calculation efficiency is improved, and the storage cost is reduced. The application satisfies adaptive IND-ID-CPA security under a standard model, has unidirectionality and limited multi-hop nature, and can resist collusion attacks.

The invention relates to the technical field of network security, and provides a quantitative risk assessment method and system based on real-time information flow analysis. A dynamic information flow analysis algorithm is constructed through an information flow graph model, potential threats are found through statistical anomaly detection, and finally mixed quantitative risk assessment calculation is carried out by fusing time sequence attenuation analysis and multi-factor weighted scoring. Therefore, static and passive security detection is converted into a dynamic, active and adaptive security risk assessment system, and support is provided for improving the agility and effectiveness of security defense.

The application provides a large language model adaptive security protection method and system, and a storage medium, the method breaks the hysteresis of the traditional defense strategy by constructing a three-agent collaborative architecture of an attack strategy generator, a dynamic defense device and a defense and attack environment evaluator, combining a double-layer optimization and a dynamic evolution mechanism, driving a two-way iteration relying on attack and defense utility quantitative scores, and synchronously evolving the defense capability and the attack evolution; the method constructs a double-layer defense capability for coping with the current situation and predicting the future by real-time adaptation of the defense parameters to the current attack and pre-judgment of the new attack by the defense parameter, improves the generalization to unknown attacks; the method strengthens the learning and identification of high uncertainty attacks by combining meta-learning attack evolution and threat entropy weighted loss, reduces the bypass probability of new attacks; the method balances the security and usability of the large language model by using a dynamic threshold judgment, realizes adaptive and highly reliable security protection in an open scene, and has better generalization.

Systems, methods, and computer-readable storage media. One system includes a readiness system configured to access entity data of an entity and determine a security posture of the entity based on the entity data. The system includes an incident system configured to model, based on the security posture, at least one security risk or security vulnerability. The system includes an action system configured to execute one or more actions associated with at least one entity computing system or computing network of the entity. The system includes an output system configured to provide a user interface to the at least one entity computing system or the computing network of the entity, the user interface including at least one of (i) posture data associated with the security posture, (ii) incident data associated with the at least one cyber incident, or (iii) action data associated with the one or more actions.

The embodiment of the invention discloses a non-intrusive signature encryption video playing method based on a secure decoding library. A specific embodiment of the method comprises the steps of configuring a decoding library supporting a security function in response to a situation that a target video monitoring platform does not support a preset protocol; initializing a decoding library, and transmitting the security gateway address and the target front-end equipment identifier to the decoding library; sending a video playing request to the target video monitoring platform through a transmission protocol of the target video monitoring platform, and receiving a signature encrypted video code stream from the target video monitoring platform; transmitting the signature encrypted video code stream to a decoding library; and based on the decoding library, carrying out adaptive security processing on the signature encrypted video code stream to obtain decoded video data, receiving the decoded video data from the decoding library, and playing the decoded video data. According to the embodiment, for a video monitoring platform of a non-GB35114 standard, the technical effects of reducing video playing delay and gateway load and meeting data security requirements are achieved.

The invention discloses a self-adaptive safety monitoring method and system based on uncertainty perception, relates to the technical field of operation safety monitoring, and solves the problem that the capability of identifying progressive risks in an operation scene is insufficient. According to the embodiment of the invention, by taking uncertainty as a risk signal and combining an uncertainty accumulation mechanism, a low-confidence abnormal mode which cannot be captured by a fixed threshold value can be sensitively perceived, so that early warning is given at the early stage of the risk, and precious gold response time is provided; after a risk early warning signal is sent out, a corresponding deep analysis sub-graph is selected, historical audio and video data before a risk occurs are subjected to refined redisk by using the strong understanding capability of a multi-modal large model, a risk evolution process is reproduced, a root cause is positioned, and a high-quality analysis report is output. The defect that the output result of a traditional scheme lacks process information is overcome.

The invention relates to a dynamic authorization method based on a software defined boundary and a user behavior baseline, and belongs to the field of network security. According to the method, initial strong authentication of a software defined boundary SDP is combined with continuous monitoring based on a user behavior baseline, and a dynamic authorization system throughout the full life cycle of a session is constructed; the abnormal risk is identified by comparing the current operation of a user with a dynamically updated behavior baseline in real time, and an authorization engine is triggered to automatically execute a complete method flow of authority adjustment according to the risk alarm, so that the fundamental conversion from'one-time authorization 'to'continuous self-adaptive authorization' is realized. According to the method, on the basis of a controlled channel established by the SDP, continuous learning and risk assessment of behaviors in a user session are introduced, and the access authority is automatically adjusted in real time according to an assessment result, so that a self-adaptive security closed loop integrating perception, analysis, decision making and execution is formed.

The invention discloses a blockchain data-driven zero-knowledge proof intelligent security protection method and system, and belongs to the technical field of blockchains, and the key point of the technical scheme is that a layered architecture design is adopted, the system comprises a data layer, an analysis layer, a proof layer and a protection layer, and the layers cooperate to realize intelligent and adaptive blockchain security protection. According to the method, block chain data analysis and a zero-knowledge proof technology are organically combined, and automatic security policy execution is realized through the smart contract. The system firstly trains a protection model based on historical transaction data, and identifies an abnormal transaction mode; when a suspicious transaction is detected, a zero-knowledge proof verification mechanism is triggered, and a transaction initiator is required to provide a corresponding validity proof; meanwhile, the system can dynamically adjust security strategies and protection measures according to changes of attack modes, and the intelligent and self-adaptive security protection effect is achieved.

This invention relates to the fields of cloud computing and identity authentication security technology, and discloses a method and system for cross-domain intelligent identity authentication in a cloud environment. The method includes: collecting and preprocessing heterogeneous identity data from multiple cloud platforms to obtain a standardized identity dataset; constructing a unified identity semantic model based on the standardized identity dataset and generating feature embedding vectors; performing identity mapping transformation on the feature embedding vectors using a deep neural network to obtain mapped identity feature vectors; performing multi-factor adaptive trust assessment by combining the mapped identity feature vectors with real-time behavioral data to obtain dynamic trust assessment results; generating an adaptive security token based on the dynamic trust assessment results; and converting the adaptive security token into the protocol format required by the target system. This invention can solve the problems of heterogeneity and dynamic trust assessment in cross-domain identity authentication in a cloud environment, providing an effective solution for cloud computing security.

This application discloses an online detection and rejection system, method, and computer-readable storage medium for automated warehouse pallets. The system includes: a detection module for acquiring three-dimensional geometric data of pallets to be received online; a data processing and judgment module for comparing the acquired three-dimensional geometric data with preset standard pallet data, and determining an abnormal pallet and generating an abnormal signal when the detection deviation exceeds a preset threshold; this module can also evaluate structural integrity based on partition weighting and calculate the center of gravity offset vector; a scheduling system for receiving abnormal signals and locking abnormal pallets; and execution equipment, including automated guided vehicles or sorting mechanisms, for removing abnormal pallets according to the schedule. This application enables high-precision online detection and quantitative damage assessment of incoming pallets, and adaptive safety control of the handling process based on defect data such as center of gravity offset, improving detection accuracy and the overall safety of automated warehousing operations.

The invention relates to the technical field of power grid dispatching automation, in particular to an intelligent dispatching operation ticket generation and error prevention method and system based on natural language processing and real-time topology simulation, and the method comprises the steps: analyzing a natural language instruction into a structured operation task through a special semantic understanding model in the power dispatching field; based on real-time topology and power flow data of a power grid, an optimal operation sequence is dynamically generated through a generation engine fusing graph search and power flow sensitivity analysis, and real-time simulation and safety early warning are carried out through a dynamic anti-error checking engine; historical operation logs are mined through a reinforcement learning model, and self-evolution of an anti-error rule and a generation strategy is achieved; the system comprises a semantic understanding module, a dynamic generation and error prevention module and a knowledge self-evolution module. The problems that in the prior art, labor is relied on, efficiency is low, and the anti-error capability is static and rigid are solved, and whole-process intelligentization and self-adaption security of operation ticket dispatching are achieved.

The invention discloses a self-adaptive security policy evolution method, system and device and a storage medium. Collecting heterogeneous log data, and mapping the heterogeneous log data into standard tetrad data; analyzing the streaming security events through a PCMCI and NOTEARS mixed causal discovery algorithm, identifying a time-lag causal relationship between attack behaviors, and constructing a dynamic causal map; fusing external asset attribute information, performing risk propagation prediction by using a time sequence diagram neural network, and outputting a future attacked probability of each node; inserting the security policy into the atlas, constructing a heterogeneous graph containing risks and policy nodes, optimizing a reinforcement learning model based on a constraint policy, and generating a policy adjustment action; a strategy is defined as an infrastructure code, security execution is carried out through a gray release mechanism, and automatic rollback of a monitoring index is realized; and finally, collecting feedback data, and carrying out online updating on the prediction and decision model to form a closed-loop self-evolution system. According to the invention, rapid, automatic and precise closed-loop evolution of the security policy is realized.

Systems, methods, and computer-readable storage media. One system includes one or more processing circuits configured to identify one or more proofs of a security posture of at least one entity, receive a selection corresponding to at least one third-party protection parameter, update the computing infrastructure of the at least one entity based on the at least one third-party protection parameter, detect a cybersecurity incident associated with the at least one entity, and provide, to at least one interface or dashboard, incident data associated with the cybersecurity incident, wherein the at least one interface or dashboard includes one or more states or statuses of the computing infrastructure based on the incident data and the security posture.

The application provides a kind of based on the cooperative jamming security transmission method and system of transmissive-reflection integrated smart surface, belongs to wireless communication technical field, the method includes: constructing security communication scene;In the security communication scene, transmissive-reflection integrated smart surface with the function of re-regulating incident signal into transmission signal or reflection signal is deployed, to divide the communication space into transmission space and reflection space;In different communication link scenes, combined with the cooperative jamming security transmission method, different security communication strategies are set;The communication performance key parameters of each security communication strategy are calculated and analyzed, to select the required security communication strategy according to actual demand.The application uses transmissive-reflection integrated smart surface to construct security communication scene that can not only guarantee communication efficiency but also effectively defend against eavesdropping attacks, not only enhances the security of communication system, but also provides an important idea for future intelligent, adaptive security communication network design.

The invention relates to an intelligent security and protection system and method for an insurance document warehouse. The system comprises a multi-sensor sensing network, a security and protection risk decision module and a security and protection response module. The multi-sensor sensing network collects multi-sensor data of a target insurance document warehouse and uploads the multi-sensor data to the security risk decision module; the security risk decision-making module performs calculation based on a preset dynamic risk decision-making algorithm in combination with multi-sensor data to obtain a comprehensive risk score value of the target insurance document warehouse; and the security response module performs hierarchical adaptive security response on the target insurance document warehouse according to the comprehensive risk score value. The multi-sensor data is comprehensively analyzed through the preset dynamic risk decision algorithm to obtain the comprehensive risk score value, and the comprehensive risk score value performs hierarchical adaptive security protection response on the target insurance document warehouse, so that early, accurate and active intervention on the security protection risk of the insurance document warehouse is realized.

The application belongs to the technical field of intelligent power internet of things, and particularly relates to a method for adaptive security access of unmanned aerial vehicle (UAV) heterogeneous terminals for power edge computing, and the specific steps are as follows: terminal registration and trusted anchoring, binding hardware-level identity, collecting multi-modal fingerprints, and constructing a security behavior portrait; adaptive access authentication; dynamic behavior monitoring and baseline adjustment, establishing an identity authentication and management system, synchronously performing multi-dimensional real-time monitoring, linking and disposing abnormal behaviors, and adopting a baseline evolution mechanism to avoid misjudgment; the multi-dimensional real-time monitoring includes terminal business trend monitoring and traffic situation analysis; security closed loop and collaborative response. The application can realize unified risk detection of the UAV, real-time monitoring of vulnerabilities, access permissions and running states of the UAV, construction of a dynamic behavior monitoring model in combination with UAV terminal information, business data, environmental data and the like, and real-time monitoring and early warning of the UAV terminal.

This invention discloses a data security access control method based on symmetric encryption, comprising the following steps: collecting access requests to generate access event sequences; constructing an access behavior graph, binding symmetric key increments, and generating access behavior graph data; calculating multi-scale topological feature encodings into an access behavior fingerprint set, and generating the region to which the access behavior fingerprint belongs; generating an attacker's cognitive state vector; calculating the session information leakage amount and generating an information leakage budget state; selecting a symmetric key subspace and generating a path working key; dividing encrypted data into a semantic field set and generating a candidate access view set; and executing data security access control: when authorized, selecting the authorized view to decrypt and generate the target data access view; when unauthorized, selecting the decoy view to generate the decoy data access view. This invention utilizes access behavior fingerprints and dynamic key control to achieve adaptive secure access control of encrypted data, possessing advantages such as strong anti-inference capabilities, high misleading potential, and refined authorization.

The invention relates to the technical field of data traceability, provides a fine-grained data sharing traceability method and system based on attribute encryption and a block chain, and solves the problems of rough authorization granularity and difficult traceability caused by static role division and a loose evidence storage mechanism. The method comprises the following steps: acquiring fine-grained data in a data sharing scene; processing the data main body data, adjusting the initial permission mapping rule to obtain a target permission mapping rule, generating a permission control rule and obtaining a target data access record; encrypting the fine-grained data to obtain target encrypted data and a decryption key; performing classified storage on the target encrypted data according to the authority control rule to obtain classified storage data; and distributing the target data access record, the decryption key and the classified storage data to corresponding evidence storage nodes of the block chain for evidence storage, and generating a traceability result in combination with permission verification logic. According to the method and the device, fine-grained, traceable and trust dynamic change-adaptive security data sharing can be realized.