4138 results about "Information security" patented technology

The invention discloses a data security dynamic evaluation system and a protection method, belongs to the technical field of information security, and is used for solving the problem of terminal equipment access control and behavior risk dynamic collaborative protection. The method comprises the following steps: generating fingerprints through terminal equipment features, verifying authorization, inputting access feature slices into a time sequence model by authorized terminal equipment, generating a trust score based on cosine similarity of a behavior sequence and a prediction sequence, and constructing a Markov model to dynamically select an authentication mode according to the trust score; calculating a risk index by combining network and geographic information, and distributing the risk index to a real or virtual environment; and the unauthorized terminal equipment distributes the virtual environment after registration. Differentiated monitoring is carried out, a time sequence library is established in the virtual environment, and doubt scores are generated through sequence matching; the state deviation of the real environment is calculated through a hidden Markov model, and the risk score is generated by fusing the multi-dimensional features. And based on the result management authority, the suspicion terminal equipment isolates and shrinks the authority, the compliance terminal equipment authenticates and migrates, and the access is regulated and controlled according to the minimum privilege principle and the time window mechanism.

The invention discloses an information security adaptive protection method and system based on artificial intelligence, and relates to the field of security protection, and the method comprises the steps: dynamically collecting multi-dimensional asset data through distributed nodes, carrying out the edge calculation preprocessing, and extracting features through a deep learning model; carrying out threat identification by fusing LSTM time sequence analysis, an isolated forest and a multi-modal AI detection engine of a knowledge graph; outputting a risk level based on an improved analytic hierarchy process and a fuzzy evaluation model; the AI strategy engine combines the risk level and the business scene to generate an optimal protection strategy, and continuous optimization is carried out through reinforcement learning; a standardized instruction is linked with safety equipment to execute protection, and interception effect closed-loop optimization is fed back in real time; a whole process log is stored through a block chain, and an attack evidence chain is generated through an AI traceability model. The method has the advantages that the information security protection capability is comprehensively improved through hierarchical data acquisition, multi-modal threat detection, scientific situation evaluation, dynamic generation of an optimization protection strategy and combination of block chain evidence storage and AI traceability.

The invention relates to the technical field of network and information security, and discloses a multi-source security information collaborative analysis method and system fused with an AI intelligent agent, and the method comprises the steps: collecting security related data; cleaning and normalizing the collected data, and extracting target security features from the preprocessed data; constructing a plurality of AI agents for different data sources, and generating a preliminary threat judgment result through semantic understanding, behavior pattern recognition and association rule mining based on target security features; performing time sequence fusion on the preliminary threat judgment result, constructing a dynamic security situation model, capturing a threat evolution trend, and dynamically determining a risk level and a priority processing sequence of an event in combination with threat intelligence; according to the risk level and historical response experience, the AI intelligent agent generates an automatic response suggestion and pushes the automatic response suggestion to operation and maintenance personnel; according to the invention, the threat identification capability is improved.

The invention discloses a public opinion risk assessment method and system based on multiple agents and a large language model, and belongs to the technical field of network information security. The method comprises the steps of obtaining multi-source public opinion data; reasoning in combination with a language model to obtain a multi-dimensional semantic vector, and clustering to form a plurality of topic clusters; the emotion opposition level, the credibility and the text quantity increment score of each topic cluster are generated based on an intelligent agent, a comprehensive risk value is obtained through weighted fusion, and high-risk topics are screened through a double-threshold retention mechanism; and generating a knowledge graph according to the high-risk topic, determining an associated entity, a propagation link and an intervention node, implementing an intervention strategy, and generating a public opinion intervention report. According to the method, the monitoring problem of multi-source heterogeneous public opinion data can be effectively solved, the accuracy and timeliness of risk assessment are improved, full-link automation from risk identification to accurate intervention is realized, and efficient support is provided for public opinion management and control of governments, enterprises and other mechanisms.

The invention discloses a dynamic sensitive information filtering system and method based on context semantic understanding, and relates to the technical field of information security and natural language processing. Comprising the steps of 1, creating a dynamic sensitive information filtering system, 2, carrying out cleaning, structuring and standardization processing on an input text through a text preprocessing module, 3, capturing deep semantic features of preprocessed text data through a semantic feature extraction module by utilizing a deep learning model, constructing a context-associated semantic representation space, and carrying out dynamic sensitive information filtering on the context-associated semantic representation space. 4, performing multi-level sensitive information detection based on the semantic features through a sensitive information identification module, and identifying the type, the position and the risk level of the sensitive content; 5, on-line iteration of knowledge base and model ability is carried out through a dynamic updating module to cope with dynamic changes of sensitive information types, and 6, safety disposal is carried out on detected sensitive information through a result output module, a filtering result is output, auditing tracing ability is provided, and the auditing tracing ability is provided. And 7, forming a system optimization closed loop through a feedback mechanism module according to user feedback and manual auditing, wherein the system optimization closed loop is used for continuously improving the detection accuracy and adaptability.

The invention relates to the technical field of network and information security, in particular to a zero-trust multi-party security data exchange method, which comprises the following steps of: generating a zero-trust token and a capability authorization bill and constructing context description data; authentication encryption is performed on the plaintext fragment, attribute-based encryption is performed on the data one-time key, and a policy bearing ciphertext container is assembled; in the trusted execution environment, authentication decryption is completed through a one-time secret key of data recovery through joint challenge and threshold deblocking, or strategy migration and transfer are achieved through proxy re-encryption; and aggregating the decryption event and the forwarding event by vector commitment, generating a time anchor, and mapping the time anchor into a next round of random base. According to the invention, fine-grained authorization of the key layer, no plaintext transfer, event-level verifiable auditing and rapid revocation are realized.

The invention belongs to the technical field of artificial intelligence and information security crossing, and discloses a multi-modal false news detection method based on decoupling and cross-modal clue mining, and the method comprises the steps: employing a pre-training comparison model to extract text and image features in news, and mapping the text and image features to a unified embedding space; designing a multi-modal decoupling automatic encoder, decomposing each modal feature into modal common and modal specific representation, and obtaining a pure decoupling feature through confrontation constraint and reconstruction loss; a cross-modal clue mining module is constructed, modeling complementation is carried out from non-unhooked features, and conflicting semantic clues are enhanced; a self-adaptive attention aggregation module is introduced, and the modal features and the semantic clues are dynamically weighted and fused; and inputting the aggregated representations into a classifier for false news identification. According to the method, through modal decoupling and multi-source clue modeling, modal redundancy and specific information are effectively separated, association and conflicts between images and texts are deeply mined, and the detection accuracy is remarkably improved.

The invention provides an intelligent data security exposed surface risk assessment method, system and device and a medium, and relates to the technical field of information security, and the method comprises the steps: constructing an exposed surface asset map through an asset fingerprint recognition engine, and calculating an asset exposure index; constructing a vulnerability knowledge base, and identifying potential vulnerabilities; based on the standard vulnerability score, the vulnerability utilization tool activeness and the attack event frequency in the set time period, calculating the triggering probability of the potential vulnerability as a dynamic vulnerability score; malicious IP access frequency and leakage record matching degree are obtained through firewall logs and dark web monitoring data, and threat intelligence factors are obtained through calculation; calculating an exposed surface risk value in combination with the asset exposure index, the dynamic vulnerability score and the threat intelligence factor; and based on a time decay model, according to the exposed surface risk value and the business influence factor, calculating a residual risk value, and obtaining an exposed surface risk assessment result. The accuracy of risk assessment is further improved through multi-dimensional data fusion.

The invention discloses a power grid material sampling inspection management method for realizing whole-course tracing based on intelligent sample sealing, and relates to the technical field of electric power material management and intelligent perception, and the method comprises the following steps: S1, an initialization stage: executing a sample sealing coding segmentation pre-configuration process, distributing independent numbered segments to each sample sealing terminal, and the central control module synchronizes the use state of the terminal code to realize distributed isolation of code generation. According to the invention, coding uniqueness is realized through segmented pre-configuration and global duplicate checking, identity information security is guaranteed by adopting chip one-time write protection and tamper-proof technologies, and sample packet switching and data counterfeiting are effectively prevented by combining automatic acquisition and multi-round consistency comparison. Abnormal recognition and closed-loop processing ensure that abnormal events are frozen in time and responsibility is traced, and irregular samples are prevented from flowing into subsequent links. The whole-process auditing and dynamic optimization enable the management process to be self-perfected, and the intelligence, standardization and reliability of sampling inspection of the power grid materials are remarkably improved.

The invention relates to the technical field of enterprise data encryption, and discloses an enterprise data encryption method and system based on artificial intelligence, and the method comprises the steps: collecting internal and external heterogeneous data streams of an enterprise, carrying out the standardization processing, and recognizing potential risk features through combining time sequence alignment and vulnerability analysis; a risk probability analysis tool is utilized to carry out quantitative evaluation from two dimensions of data sensitivity and an influence range, an encryption parameter adjustment scheme is dynamically generated, calculation and storage resources are dynamically allocated according to a scene risk level, an encryption strategy is updated in real time, and hierarchical protection is carried out on sensitive information. According to the method, corresponding encryption strength can be adopted for data of different risk levels, resource utilization is optimized while safety is guaranteed, the data leakage risk is effectively dealt with, and the enterprise information safety protection capability is improved.

The invention discloses an information physical security defense method, system and device based on a distribution network digital twin simulation platform and a medium, and belongs to the technical field of information security and control defense of the power distribution Internet of Things, and the method comprises the steps: constructing a three-dimensional channel for interaction of a physical power grid, an information model and simulation data; on the basis of a three-dimensional channel, a three-state dynamic conversion model among a steady state, a transient state and a recovery state is constructed, and multi-state automatic switching simulation is achieved through sub-region division and parallel computing; a multi-level risk modeling system oriented to various risks is constructed based on simulation results, complex attack scenes are identified, and mapping of risk types and response paths is achieved; security risk assessment and defense strategy generation verification are completed, and intelligent collaboration and continuous learning of cross-domain defense strategies are achieved through collaborative optimization. According to the method, the construction efficiency of a complex risk scene is improved, quantitative analysis of cross-domain risks such as circuit breaker mis-tripping caused by network attacks is realized, and the limitation of traditional single-domain risk analysis is broken through.

The invention discloses an MES (Manufacturing Execution System) login authentication method based on a face recognition technology, which relates to the technical field of industrial information security, and comprises the following steps of: constructing an authentication data acquiring a face image of an authorized user of an MES, extracting a reference face feature template after preprocessing, and constructing the authentication database; performing associated storage on the reference feature template, user identity information, preset operation authority and affiliated production station information to form an authentication database; according to the method, spoofing attacks are prevented through multi-mode living body detection, and the problem that a traditional password / key is easy to leak and borrow is solved in combination with uniqueness of human face biological characteristics; a person-post-terminal binding mechanism further limits permission abuse, and internal operation risks are reduced; the non-contact authentication does not need to memorize a password or carry a physical key, and is suitable for a working scene that a workshop operator wears gloves and holds tools; and the recognition passing rate in a complex industrial environment is improved through dynamic threshold optimization.

The invention discloses a network security situation awareness and analysis platform based on AI, and relates to the technical field of network security situation awareness and analysis, and the platform comprises a multi-source data collection module which integrates flow, logs, assets and threat intelligence data, and carries out encryption transmission and standardization; the data preprocessing module purifies and optimizes data, and guarantees data quality and sensitive information security; the AI situation awareness analysis module extracts features through a deep learning model, dynamically evaluates the situation and identifies threats; the threat early warning and decision-making module triggers graded early warning and generates a targeted emergency response scheme; the visual display and interaction module displays information in multiple dimensions and supports query and report generation; and the data storage and tracing module adopts a mixed storage architecture, so that the data security and traceability are ensured. The platform integrates multi-source data and realizes situation accurate perception and intelligent decision by means of an AI technology; the early warning is accurate, the visual interaction is convenient, and the intelligent and efficient level of network security protection is comprehensively improved.

The invention discloses a communication terminal and a communication terminal marking method. A communication terminal according to an embodiment of the present invention comprises: a receiving unit for receiving tag information; the safety carrier is connected with the receiving unit so as to acquire the mark information; the security carrier uses preset verification information to verify the mark information, and after verification is passed, mark data is generated according to the mark information; the container unit is used for receiving and storing the marking data, and the marking data is used for marking information interacted with the outside world. According to the communication terminal and the communication terminal marking method provided by the embodiment of the invention, the marking data can be safely stored.

The invention discloses a dynamic key threshold fragmentation privacy tracing method based on block chain collaborative verification, and belongs to the field of information security. According to the method, a dynamic key is taken as a hub, decentralized identity, zero-knowledge verification, deep watermark and threshold collaborative decryption are deeply coupled, a temporary key generated by each conference is split into a plurality of fragments, the fragments are stored in a distributed manner by a block chain node and a tracing unit, only a hash fingerprint combined by the fragments is subjected to chaining and evidence storage, and the dynamic key is subjected to zero-knowledge verification and deep watermark and threshold collaborative decryption. A light evidence chain which cannot be tampered but has no privacy exposure is formed; participants are anonymously accessed through a verifiable certificate without leaking specific information, and truth of anonymous identity is ensured through signature of a trusted unit; when data leakage occurs, the tracing unit extracts a watermark, compares a zero knowledge proof, verifies the relevance between a leaked ciphertext and a chain fingerprint, triggers a multi-party threshold decryption recovery key, and finally accurately positions a person in charge in combination with the encrypted and stored DID mapping table without exposing irrelevant information in the whole process.

The invention discloses a government affair department knowledge base access authority control method based on a block chain, and relates to the technical field of block chains and information security, distributed nodes jointly participate in decision making, the performance bottleneck of a single control point and the single point fault risk are effectively eliminated, and the reliability and stability of a system are remarkably improved; when a plurality of departments need to collaboratively update a strategy, the intelligent contract based on the threshold multi-signature mechanism can automatically execute voting aggregation and a strategy effective process without depending on manual operation of a central administrator, so that the efficiency and the automation level of cross-department collaboration are greatly improved, and the instantaneity and the consistency of strategy change are ensured; the inherent non-tampering and traceable characteristics of the block chain provide powerful auditing guarantee for the whole authority management process; and each policy update request, voting process, final decision and policy version switching are completely recorded on the chain to form a non-repudiated audit clue.

The invention relates to the technical field of information security management, and discloses an information security management method and system based on digital medical treatment. The method comprises the following steps: verifying doctor professional qualification, patient authorization range, data sensitivity level and time permission validity in a multi-institution medical data access request, and generating a permission verification result; analyzing ontology semantic attributes and sensitivity characteristics of medical search keywords input by a user, and determining a corresponding hierarchical encryption strategy based on the permission verification result; performing homomorphic encryption transformation on the medical term synonym set according to the hierarchical encryption strategy, and constructing a medical ciphertext database; and receiving a medical query request, executing symptom disease association matching and ciphertext state logical reasoning operation in the medical ciphertext database, and outputting an encrypted state search result. According to the method, the privacy leakage risk caused by search behavior trajectory analysis is effectively prevented, and the security and availability of medical data are improved.

The invention discloses an energy big data right confirmation method and system based on a hierarchical hash tree and dynamic authorization, and belongs to the field of energy big data management and information security, and the method comprises the steps: obtaining and standardizing original data in an energy scene, and dividing the original data into a data block set according to equipment and time; constructing a hierarchical hash tree and generating root hash; writing the root hash and the associated metadata into the block chain to realize right confirmation and evidence storage; executing proxy re-encryption according to the access token, and converting the ciphertext into a decryptable format; verifying the data consistency through the Hash path and the root Hash, and completing the access; and recording the access behavior and distributing transaction earnings by the smart contract based on the contribution degree. Hash calculation and local path updating of a data block level are supported through a layered Hash tree structure, so that when large-scale energy data is frequently updated, a new root Hash value can be quickly generated and right confirmation updating can be completed only by carrying out local Hash recalculation on a changed path.

The invention belongs to the technical field of information security, and discloses an NLP verification method for a commercial password security assessment report based on an agent. The comprehensive consistency verification of the assessment report is realized by constructing a cryptographic term knowledge graph, generating a cross-chapter cryptographic parameter consistency verification matrix, identifying security statement conflict points and constructing a report internal logic conflict detection model. And adopting a multi-agent cooperation mechanism to carry out iterative optimization on a verification result, and outputting a structured verification report containing contradictory position indexes and type labels. According to the method, the consistency verification capability of the password evaluation report is improved, dominant parameter inconsistency and hidden semantic conflicts can be accurately identified, the auditing cost is reduced, and the wrong implementation risk caused by report inconsistency is prevented.

The invention relates to the technical field of information security, in particular to a security baseline setting method and system equipment based on clustering decision and a medium, and the method comprises the steps: collecting original data, carrying out the construction of a feature vector through feature conversion, generating a sample, and marking and extracting the sample; constructing a classification model by using manifold learning, inputting the extracted feature vectors into the constructed classification model, optimizing the model through training, and outputting classification labels; processing the decision boundary by using constraint optimization and feature scaling to obtain a standardized feature vector converted by a decision boundary model, grouping based on the standardized feature vector, and extracting a baseline; the security policy is generated through data analysis, and the data is dynamically updated and continuously monitored, so that the unified configuration and centralized management of the security policy are realized, and the policy implementation efficiency and the system expansibility are remarkably improved.

The invention discloses a power system data access management and control system based on risk dynamic assessment, and particularly relates to the technical field of power system information security and access control. Comprising an access request interception module, a multi-dimensional risk data acquisition module, a dynamic risk assessment engine module, a self-adaptive access control decision module and a security audit and learning module. Multi-dimensional dynamic context information such as an access subject, an object, an environment and a behavior sequence is collected in real time, a rule engine and machine learning hybrid model is combined to carry out real-time risk calculation, a quantitative comprehensive risk value is output, and an access control decision is dynamically generated according to a risk level threshold. The system has self-learning and self-adaptive optimization capabilities, continuously optimizes the model through an audit log, improves the security and flexibility of data access of the power system, and balances service availability and security protection requirements.

The invention discloses a computer file protection method, which relates to the technical field of computer information security, and comprises the following steps of: S1, classifying files and marking security levels based on content characteristics and sensitivity; s2, dividing system user permission levels and configuring a multi-factor authentication mechanism; s3, constructing a file access control matrix and setting a fine-grained operation authority rule; s4, deploying an access behavior monitoring module, and recording a file operation behavior log in real time; s5, performing dynamic risk analysis based on behavior modeling and an anomaly recognition algorithm; s6, performing hierarchical response according to the risk level, wherein the hierarchical response comprises measures such as warning, limiting, network disconnection and locking; and S7, encrypting and storing the log information, and providing an auditing interface for behavior traceability. According to the method, static permission control and a dynamic behavior recognition mechanism are fused, full-process intelligent protection of files from creation, access, transmission to storage is achieved, and the method has the advantages of being high in safety, timely in response, capable of achieving self-adaptive evolution of strategies and the like.

The invention relates to the technical field of information security, in particular to a user information protection method and device based on a dynamic desensitization strategy, and the method comprises the steps: determining sensitive data and a sensitivity score thereof through a named entity recognition model and a sensitivity scoring algorithm, extracting scene parameters, and determining a scene risk score through a risk quantification algorithm; and then a dynamic desensitization strategy generation algorithm is called to generate a target desensitization strategy, and finally, the strategy is used for desensitization and a reversible desensitization data identifier is generated. Through the series of steps, the desensitization strategy is dynamically generated according to different use scenes, the problem of scene adaptability deficiency caused by static desensitization strategy stiffness is solved, meanwhile, the reversible desensitization reduces the security risk caused by reverse cracking of rules, excessive desensitization is avoided, and the data availability is improved.

The invention discloses an attack event semantic recognition method and system for terminal log analysis, and relates to the technical field of information security, and the method comprises the steps: collecting multi-source heterogeneous log data from terminal equipment, and carrying out the preprocessing to obtain standard log data; performing structured conversion and multi-modal fusion on the standard log data to obtain fused log data; performing feature extraction on the fused log data to obtain a key log feature set; and constructing an event semantic recognition optimization model, performing semantic recognition on the key log feature set, determining attack event semantic information, and triggering attack event early warning. The technical problem of low attack event identification accuracy and real-time performance due to the fact that the existing log analysis method cannot efficiently process the multi-source heterogeneous log data is solved, and the technical effect of improving the attack event identification accuracy and real-time performance through structured conversion and multi-modal fusion of the multi-source heterogeneous data is achieved.

The invention relates to the field of digital image processing and information security, and discloses a document tampering detection method and system based on image data processing, and the method comprises the following steps: firstly, extracting the noise residual error and microscopic penetration characteristics of a document image, and constructing a physical potential energy field and a virtual viscous resistance field; performing dynamic evolution by using a Darcy law variant model to generate a virtual flow velocity vector field to simulate the slippage behavior of the fluid in the heterogeneous medium; and then a heterogeneous graph is constructed based on the flow field divergence singular points and the streamline trajectory, deep reasoning is carried out by using graph neural network aggregation node dynamic features, and finally a tampering localization mask is generated. According to the method, the fluid mechanics field theory is innovatively introduced, hidden static texture differences are converted into remarkable dynamic flow field anomalies, the problem that microscopic tampering traces are difficult to capture in the prior art is solved, and the detection precision and generalization ability in a complex document scene are remarkably improved.

The invention relates to the technical field of data acquisition and information security, and discloses a block chain tamper-proof data acquisition method and device, and the device comprises a control chip, an identity recognition module, a local tamper-proof module, a time sequence processing module (including a parallel uploading unit), a clock calibration module, a storage monitoring module and the like. The method comprises the steps of hardware-level identity verification, operator verification, generation of a data packet containing metadata, encryption and tamper prevention, networking / offline uplink evidence storage, association uplink approval and hash comparison verification. By applying the method and the system, the tamper-proofing of the data in the whole process can be realized, the offline scene is adapted, and the high-credibility data acquisition requirement is met.

The invention relates to the technical field of quantum cryptography, in particular to a dynamic key generation system and method based on multi-source QRNG and QKD, and the system comprises an interface registration method, a calling method, related equipment and a storage medium, is used for generating a high-security quantum key, and is a quantum key service system with a layered architecture. By abstracting, integrating and managing bottom-layer multi-source QRNG and QKD equipment and fully utilizing the flexible scheduling of quantum equipment, the security of key generation is ensured, so that the key service has higher performance, usability and security, and unified, dynamic and high-security quantum key generation and supply services are provided for various applications of the upper layer. The method is widely applied to the industries and fields of government, finance, energy, traffic, electric power and the like, meets the requirements of quantum key acquisition of various business applications in cloud computing and non-cloud environments, and ensures information security and business continuity.

The invention relates to the field of information security, and provides a symmetric encryption key secure transmission method and system. The method comprises the following steps: acquiring a unique fingerprint of equipment and a system parameter, and deriving the unique fingerprint of the equipment and the system parameter through a Hash algorithm to generate a seed key; deriving an initial symmetric key through a Hash algorithm based on the seed key, and performing recursive calculation in combination with key update parameters to obtain a session key; generating a plurality of random components, equally dividing the session key, and then carrying out XOR operation on the session key and each random component to obtain a key fragment set; and carrying out encryption verification on the session key and the plurality of key fragments in the key fragment set, generating verification values corresponding to the plurality of key fragments, and respectively transmitting the plurality of key fragments and the corresponding verification values through a plurality of different transmission paths. According to the invention, dynamic derivation and secure fragmentation transmission of the symmetric key without hardware protection and asymmetric encryption are realized, and the system security is improved.

The invention provides a dynamic traceability identifier generation and verification method based on multi-node environment data fusion, and relates to the technical field of information security and Internet of Things data credibility. The method comprises the following steps: firstly generating a seed identifier, then collecting environment data through each node to construct a multi-dimensional vector and carrying out weighted fusion, after serialization, generating a dynamic hash identifier by combining with an upper-level identifier, and meanwhile, introducing an offline trusted evolution, time drift tolerance and self-adaptive risk control mechanism; and finally, backtracking the traceability chain through recursion verification, and guaranteeing privacy in combination with zero-knowledge proof. The method solves the problems that a static traceability code is easy to copy and the data credibility is low, achieves the dynamic anti-counterfeiting and tamper-proofing of the traceability identifier, enables the digital identifier to be strongly associated with physical circulation, improves the credibility of the traceability process, can automatically find abnormal circulation and give an alarm, and is suitable for a commodity traceability scene.

The invention discloses a dynamic S-box and cross-channel diffusion image encryption method based on six-dimensional hyper-chaos driving, and belongs to the field of information security, and the method comprises the implementation steps: 1) constructing a novel six-dimensional hyper-chaos system; 2) constructing a cross-channel diffusion scheme based on the six-dimensional hyperchaotic system; 3) constructing a dynamic S box library based on a six-dimensional hyperchaotic system; according to the invention, by introducing an inter-channel coupling mechanism, the potential safety hazard of traditional sub-channel encryption is effectively relieved. A dynamic S box generated based on chaotic system state self-adaption enhances the nonlinear confusion characteristic, and Arnodcat mapping transformation realizes global pixel scrambling. Theoretical and experimental results show that the method overcomes the limitation of a low-dimensional system, and the aspects of statistical analysis, key sensitivity, attack resistance and the like are remarkably improved.