9605 results about "Information security" patented technology

The invention discloses an information security management method based on data processing, and particularly relates to the field of information security management, comprising multi-source heterogeneous data acquisition, multi-dimensional feature index calculation, comprehensive threat detection calculation and adaptive threat decision. According to the method, the covert communication channel is accurately identified by constructing the encrypted traffic multi-mode detection model and combining protocol fingerprint entropy and traffic self-similarity analysis; an improved entropy weight fusion algorithm is adopted, collaborative analysis of system process abnormity, network behavior offset and hardware degradation is achieved, and a cross-dimension attack chain is reconstructed; a storage medium physical feature-cryptographic module runtime joint monitoring mechanism is created for the first time, hardware layer physical attacks and cryptographic side channel vulnerabilities are synchronously defended through temperature-delay correlation evaluation and key derivation density analysis, a complete attack surface from a physical layer to an application layer is covered, and the security is improved. And the detection precision and the response real-time performance of the complex threats are obviously improved.

The invention discloses an electronic signature security management method and system based on a block chain, and relates to the technical field of information security, and the method comprises the steps: generating a public key and a private key of a user through a quantum resistant encryption algorithm, binding the public key with the identity of the user, recording the public key and the identity of the user on the block chain, and storing the private key through HSM hardware encryption equipment; the method comprises the following steps: standardizing a to-be-signed document to generate a standard document, and calculating the standard document through a Hash algorithm to obtain a document Hash value; the signer signs the document hash value by using a private key and a CRYSTALS-Dillitium signature algorithm, generates an electronic signature and a signature proof, associates the electronic signature, the signature proof, the document hash value and a timestamp with a public key, and records the associated information on the block chain; and the standardized processing rule is written into the smart contract, and after a verifier submits a verification request, document hash value comparison, signature effective state check and signature proof verification are carried out through calling chain data by the smart contract.

The invention relates to the technical field of information security, in particular to a power distribution Internet of Things cloud side end collaborative interaction security protection system, which comprises a network flow monitoring module, an abnormal flow identification module, a security threat response module, a network attack early warning module, a behavior pattern analysis module and an access authority management module. According to the method, the network flow data is collected and analyzed in real time, the abnormal flow recognition speed and accuracy are enhanced, the security threat response speed and efficiency are improved, measures are taken in time at the early stage of a problem, the risks of data leakage and network attacks are reduced, and the timeliness of defense measures is improved by combining security threat response and network attack early warning; by analyzing the relevance between threat events, the complex multi-stage attack activity is effectively predicted and identified, the access data and the communication mode of the equipment are monitored in real time, and the access authority and the trust level are adjusted, so that the security protection is more targeted and flexible, and the management efficiency of the risk equipment is improved.

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

The invention relates to the technical field of network security, in particular to a computer network information security monitoring method, system and device and a medium, and the method comprises the steps: obtaining encrypted traffic data and application log data in a network environment, and constructing a space-time associated original data set based on the encrypted traffic data and the application log data; performing protocol analysis on the original data set with the time-space association to generate a protocol fingerprint feature vector; inputting the protocol fingerprint feature vector and the application log data into a preset heterogeneous multi-modal analysis model, and obtaining a multi-dimensional security situation assessment result containing a threat level and an attack path; and based on the multi-dimensional security situation assessment result, generating a dynamic defense strategy instruction set through a reinforcement learning algorithm, and issuing a strategy instruction to a network execution node in real time. The method and the device have the effects of realizing real-time accurate detection of encryption threats and constructing a dynamic defense system with balanced security and efficiency.

The invention relates to a network information security protection method and system based on artificial intelligence dynamic defense. The method comprises the following steps: constructing a multi-level security policy library containing basic defense, scene defense and emergency response based on preprocessed network data features (including protocol features, behavior sequences and abnormal indexes); then, combining real-time threat intelligence and a network environment state, and utilizing a strategy combination optimization algorithm to generate a weight matrix reflecting strategy priorities and dependency relationships; dynamically extracting and fusing various defense strategies from a strategy library according to the weight matrix to form a customized defense scheme; and eliminating resource competition and logic contradiction between strategies through a conflict detection mechanism, and finally deploying a conflict-free optimization scheme to a target node. By adopting the method, collaborative deployment of multi-dimensional security policies can be realized, and the accuracy and real-time performance of security protection in a complex network environment are remarkably improved.

The present invention discloses a post-quantum key negotiation system and method based on the IKE protocol, which relates to the field of network security, especially the design and implementation of key exchange and identity authentication protocols. The present invention provides security for data protection and identity authentication by combining the IKE protocol scheme with the post-quantum cryptographic algorithm; by introducing post-quantum cryptographic algorithms such as ML‑KEM, ML‑DSA and FALCON, the quantum resistance of key exchange and identity authentication is enhanced, and the flexibility and adaptability of the protocol are also improved; in addition, the dynamic algorithm selection mechanism adopted by the present invention enables users to optimize security performance according to specific needs, thereby improving the overall efficiency of the system while ensuring information security.

The invention relates to the technical field of information security data processing, and discloses an information security analysis method and system based on big data, and the method comprises the steps: S1, collecting multi-source heterogeneous security related data which comprises a business log, a user behavior track, network traffic, an application program interface calling record, an identity authentication log and a real-time security data flow, preprocessing the collected data to obtain standardized data; and S2, performing entity identification, event extraction and relationship mining based on the standardized data, and constructing a cross-modal threat knowledge graph containing security entity nodes and associated edges. The method solves the problem of monitoring blind areas caused by lack of dynamic association mining capability among data in a traditional method, and particularly aims at distributed, low-frequency and multi-stage hidden attacks, the scheme can accurately recover an attack chain and identify high-risk threats through dynamic matching and path reasoning of a knowledge graph, and the method has a good application prospect. And the detection coverage rate and accuracy in a complex attack scene are remarkably improved.

The invention relates to the technical field of information security, and discloses an authentication method and system based on a Ksession shared session key MAC, and the method comprises the steps: obtaining to-be-encrypted data in a power monitoring system, dividing the to-be-encrypted data into key data and real-time data, and encrypting the key data and the real-time data; the method comprises the following steps: dynamically generating a Ksession key by using an ECDH protocol and an identity-based IBC technology, generating a message authentication code by using the Ksession key, carrying out integrity and authenticity verification on data in transmission through the message authentication code, transmitting encrypted data through a TLS / SSL protocol, and destroying the Ksession key at the end of a session; a quantum security digital certificate is generated by fusing quantum key distribution and a quantum security signature algorithm, and verification of the digital certificate is realized through a multi-party verification mechanism. The quantum security technology and the advanced encryption theory are integrated, and qualitative leap is achieved in the aspects of identity authentication, data encryption, integrity verification and access control.

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 relates to the technical field of data desensitization, in particular to an electronic commerce platform information security desensitization scheme analysis system based on artificial intelligence, which comprises a data classification module, an access evaluation module, a dynamic desensitization module and a security audit module. According to the method, the data of the e-commerce platform is intelligently classified and evaluated by adopting an artificial intelligence technology, dynamic desensitization and finer access control of the data are realized, various data access requirements can be dynamically met by evaluating the sensitivity level of the file and the security level of the access request, data processing is performed according to requirements, and the data processing efficiency is improved. The security and privacy of user data are effectively protected, through automation of security audit, the recognition efficiency of abnormal behaviors is improved, the transparency and traceability of overall data management are enhanced, through real-time analysis and response, the risk of data leakage is reduced, and the practical value of data and the fluency of service operation are kept.

The invention discloses a market supervision data security protection method and system based on a dynamic encryption strategy, and relates to the technical field of information security. The method comprises the following steps: generating an initial seed input improved four-dimensional hyperchaotic system, and generating a dynamic encryption parameter set through chaotic mapping iteration; the method comprises the following steps: carrying out adaptive fragmentation on market supervision data to be encrypted to generate a data sub-block set, carrying out dynamic S-box-based symmetric encryption on odd index sub-blocks, carrying out a chaotic stream encryption mode associated with a current dynamic sub-key on even index sub-blocks, and generating a unique quantum chaotic fingerprint for each encrypted sub-block; a searchable encryption index is jointly constructed by using a post-quantum encryption algorithm and a lattice-based encryption algorithm and is used for carrying out query operation under the condition that data is not decrypted; the encryption security, privacy protection capability and quantum computing attack resistance of the market supervision data are remarkably improved, and meanwhile, an efficient, flexible and extensible data security protection scheme is provided.

The invention relates to the technical field of information security, in particular to an archive electronic information security system which comprises an archive operation behavior prediction module, an archive data encryption and security storage module, an archive security protection strategy execution module and an archive resource scheduling and security monitoring module. According to the method, through time series data analysis, potential risk behaviors can be recognized in advance, illegal access and abnormal operation can be prevented, losses caused by human errors or malicious behaviors are reduced, data integrity and confidentiality are guaranteed, archive data are stored in blocks, encryption is carried out according to sensitivity and access frequency, and the security of the archive data is improved. Multi-factor identity verification is executed, the flexibility and accuracy of protection measures are enhanced, security vulnerabilities are reduced, priority protection of sensitive archives is ensured through real-time monitoring and resource scheduling optimization, resource waste and risk exposure are avoided, and the security of the sensitive archives is improved. And the overall safety protection capability of archive management in a complex threat environment is improved by collaborative measures.

The invention, which relates to the technical field of supply chain information, discloses a comprehensive supply chain control system comprising a transaction and collaborative service module, an order management and decision support module and a data interaction and integration module. The transaction and cooperation service module is used for processing transaction information of supply chain participants, ensuring information safety and accuracy, managing the full life cycle of a contract and performing real-time monitoring, establishing a real-time communication and cooperation project management channel, and improving cooperation efficiency; according to the invention, the transaction and collaborative service module has a significant effect, encryption processing ensures the security of transaction information, leakage and tampering are prevented, contract management is efficient and flexible, a multi-parameter evaluation optimization template reduces the default risk, a collaborative mechanism improves the collaborative efficiency of all parties, and the response speed of a supply chain is enhanced.

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 discloses a data communication method and system based on information security, and belongs to the technical field of data communication, and the data communication method comprises the stages of preparation, transmission, intrusion detection and defense, receiving verification and cleaning ending. The two parties authenticate and exchange keys during preparation; encrypting data by using a symmetric key and an AES algorithm; automatic defense is performed after intrusion detection; the receiver verifies the data; and cleaning the resources at the end, and performing log optimization on the system. According to the invention, through innovatively improving the intrusion detection and defense method, based on real-time network flow monitoring, intrusion analysis based on machine learning and an automatic defense mechanism, the detection accuracy and efficiency are greatly improved, and false alarms and missing alarms are reduced; defense capability and flexibility are enhanced, attacks are intelligently blocked and isolated, and cooperative emergency response is rapid; data communication security technology progress and expansion are promoted, and network security is powerfully guaranteed.

The invention discloses a fine-grained access control method and system based on risk identification, and belongs to the technical field of information security. According to the method, user subject attributes, behavior attributes and system environment attribute information are collected in real time, a standardized decision matrix is constructed, an interval type-2 fuzzy set (IT2FS) is used for conducting fuzzy modeling on the attributes, and an upper membership matrix and a lower membership matrix are generated. And calculating the dynamic weight of the attribute index in combination with a CRITIC method, introducing a time decay factor to dynamically correct a risk score through an improved TOPSIS method, calculating the Euclidean distance between an access request and a positive / negative ideal solution, and generating a normalized risk closeness degree. And based on the risk score and a preset threshold value, dynamically matching a hierarchical permission strategy, and adopting a static rule and a priority coverage mechanism to eliminate permission conflicts. According to the method, multi-dimensional risk assessment and dynamic weight adjustment are fused, the problems of insufficient real-time performance, subjective weight dependence and weak uncertainty processing capability in a traditional method are solved, the accuracy and security of access control are remarkably improved, and the method is suitable for scenes with high security requirements such as cloud computing and finance.

The invention relates to the technical field of information security, and discloses a data security management system and method in an intelligent power grid, and the system comprises a dynamic encryption and key management module which is used for carrying out the encryption and key management of the data of the intelligent power grid, determining an encryption algorithm according to the sensitivity of the data, and generating a corresponding key, the dynamic encryption and key management module transmits encrypted data and key information to the adaptive access control module so as to ensure the security of data access; and the self-adaptive access control module is used for managing access permissions of the user and the equipment and performing dynamic authorization according to the attribute label and the context information. Through dynamic encryption and adaptive key management, an encryption algorithm and a key length are adjusted in real time according to data sensitivity and a network environment, a quantum key distribution technology is combined, high security and quantum attack resistance of a key are ensured, and then security and real-time performance of data transmission are ensured.

The invention discloses an operation and maintenance question-answering system and method based on a large language model workflow, and mainly relates to the technical field of information security. Comprising a question semantic classification module used for performing semantic analysis and classification on questions through a text classification large language model when the questions are input, and identifying categories of the questions; the process selection and execution module is used for selecting and executing a corresponding process according to the semantic category of the question to generate a preliminary answer; and the answer generation and formatting module is used for processing the preliminary answers through a text generation large language model and formatting the preliminary answers into final answers which can be understood by the user. The method has the beneficial effects that the accuracy of operation and maintenance knowledge retrieval can be improved, problems can be converted into operation and maintenance instructions to execute related operations, meanwhile, the method has the capability of analyzing and deciding operation and maintenance problems, and the response quality and the capability of processing complex problems are remarkably improved.

An artificial intelligence based Offensive Cybersecurity Appliance or OCA for launching a cyber-offensive countermeasure aimed at effectively mitigating sophisticated cyber threats such as real-time Ransomware as a Service (RaaS) directives and emergent killware instigated by malicious-threat actors or cyber attackers. The system covertly uses a vast array of penetrative counter cyber attacks, based on an Advanced Persistent Threat or APT model, to circumvent encountered information security controls instituted by security-based components of a cyber attacker's Local Area Network or LAN. Intrinsically, the penetrative counter cyber attacks are constituted of multiple blended artificial intelligence based cyber attacks. The OCA subsequently uses these blended artificial intelligence based cyber attacks to render the hardware (including the cyber attacker's computer system used to instigate the cyber attack, discovered peripheral smart devices, and network-edge device such as a modem-router) interconnected to the cyber attacker's LAN inoperable by destroying the electronic components associated with that hardware.

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 relates to the technical field of CT induction power supplies, in particular to a CT induction power supply system based on cooperative control and distributed optimization and a control method. According to the technical scheme, the CT induction power supply control method based on cooperative control and distributed optimization comprises the following steps: S1, deploying a multi-mode sensing array, and synchronously collecting a three-phase current harmonic spectrum of a power supply node, an iron core magnetostriction vibration waveform and a radiator surface infrared thermal image; generating a digital twinborn body with space-time relevance through multi-physics field coupling modeling; and S2, constructing a data fusion engine driven by a space-time attention mechanism at an edge computing node, and carrying out LSTM feature extraction on the output of the step S1 and a historical operation log under physical constraint. According to the method, through collaborative innovation of multi-mode federated learning and physical embedded edge calculation, a multi-physical field dynamic modeling mechanism under privacy protection is constructed, and the correlation precision and information security of electromagnetic-vibration-thermodynamic data are effectively balanced.

The invention discloses a PUF (Physical Unclonable Function) key generation and equipment identity authentication system for a cold chain environment, and particularly relates to the technical field of information security, comprising temperature change data perception, drift modeling, dynamic error correction and closed-loop optimization, and collecting original response data of PUF hardware and temperature sensor readings by simulating the cold chain environment in a temperature-controllable experiment module; learning a nonlinear mapping relation between the dynamic temperature change and PUF response drift, and outputting a drift compensation matrix; constructing a two-stage error correction mechanism based on the drift compensation matrix; the first-stage error correction unit carries out nonlinear calibration on the original PUF response sequence according to the drift compensation matrix; the second-stage error correction unit adopts a temperature sensing type reconfigurable LDPC coding architecture, an LDPC check matrix is obtained based on a temperature-drift joint constraint model, the error correction performance of a high-drift scene is optimized through the LDPC check matrix, and the problem of key instability caused by PUF hardware response drift in a cold chain environment is solved.

The invention discloses a hierarchical use method based on sensitive data, and belongs to the technical field of data information security, and the method comprises the steps: basic data collection: obtaining overall data information which needs to be used by a demand side to the inside or the outside; identifying and preprocessing data; sensitive data storage processing: for sensitive data, storing the sensitive data in a private cloud or configuring a secret-related server; a data sensitivity evaluation model, which is used for formulating a sensitive data evaluation model according to the use route of the sensitive data through different policies; sensitive data classification processing: performing label processing on the data according to a result output by model evaluation, and providing corresponding limitation when the data is provided outwards; grading use of sensitive data; sensitive data use logs; a centralized management and control platform is used for data. According to the invention, through intelligent classification, authority control and dynamic adjustment of the access strategy, the security and compliance of the sensitive information in different use scenes are ensured.

The invention relates to the technical field of information security, in particular to a cloud-based EMM encryption method and system, and the method comprises the following steps: collecting user login data and equipment use data based on mobile equipment operation information, recognizing the time and position information of user login and equipment use, calculating the risk scores of various behavior modes, and storing the risk scores of various behavior modes. And obtaining user behavior identification data. According to the method, the comprehensiveness and the dynamism of data security management are improved by collecting and analyzing the user login data and the equipment use data in real time, identifying unauthorized access and performing risk scoring on the mobile equipment, and encryption parameters are optimized by combining real-time monitoring on the user behavior pattern and the equipment performance and utilizing data sensitivity scoring; the data encryption efficiency and security are improved, the risk of data leakage is reduced by adjusting the updating frequency and parameters of the encryption key, the response speed to security threats is improved, the flexibility of enterprise data protection is enhanced, and the service continuity is maintained.

The invention discloses a customer information management system based on enterprise information security monitoring, which relates to the technical field of information security management and comprises an information management center. The information management center is in communication connection with an information collection and storage module, an information synchronization and sharing module, a safety evaluation module, a data access monitoring module, an abnormal behavior analysis module and a risk management module, and all the modules are in electric signal connection; the information collection and storage module is used for receiving client information input by a client through a client terminal. According to the method, comprehensive risk assessment and early warning are provided by analyzing a comprehensive result of security assessment, data use monitoring and abnormal behavior analysis, so that an enterprise can identify and assess potential security risks in time and formulate corresponding risk management strategies, and the risk management efficiency is improved. The division of risk early warning levels provides a quantitative risk view for enterprises to assist the enterprises in identifying and coping with potential security threats.

The invention discloses a multi-modal knowledge question and answer retrieval method and system for a specific professional field, and belongs to the technical field of data processing. According to the method, the cosine similarity between the feature vectors is calculated in each mode through large model preprocessing to form the similarity matrix, and direct vector calculation of the problem and the knowledge base text in the professional field is realized by adopting a vectorization processing mode which is the same as that of the knowledge base text. And according to an input problem vector, through vectorization index retrieval in the professional domain knowledge base, selecting a plurality of text vectors closest to the problem vector from the professional domain knowledge base to obtain a plurality of pieces of knowledge related to the problem and the source of each piece of knowledge. According to the method, the knowledge question and answer reply accuracy of the target field is effectively improved, the knowledge question and answer reply integrity of the target field is guaranteed, basis support is realized, local deployment is supported, the information security problem is solved, and an intelligent application scene of knowledge question and answer retrieval is realized.

The invention discloses a false information detection method based on cross-modal confrontation and progressive training, and belongs to the technical field of artificial intelligence and information security. Mainly aiming at a false information detection task in a social media image-text contradiction form, a progressive adversarial training framework with multi-modal consistency constraint is provided. The core content of the method comprises: multi-modal data acquisition and processing: acquiring aligned social media multi-modal data (text, image / video); multi-modal adversarial sample generation: generating an adversarial sample based on text semantic disturbance and a visual contradiction scene; performing cross-modal progressive training, and optimizing model robustness by combining cross-modal cross attention fusion and a progressive three-stage dynamic training strategy; and generating an interpretability analysis result, and outputting an interpretability thermodynamic diagram to position cross-modal logic conflicts. According to the method, the accuracy and robustness of false information detection of the model in a multi-modal scene can be improved.

The invention discloses an information security assessment method and system based on cloud computing, and relates to the technical field of information security, and the method comprises the steps: collecting multi-modal data, and carrying out the encryption through employing a node identifier, and generating a spatio-temporal data package; the method comprises the following steps: aggregating threat features by utilizing secure multi-party calculation through edge nodes, constructing a 58-dimensional square matrix, constructing a risk assessment model based on a quantum heuristic algorithm, positioning root cause threats by applying a Do-Calculus algorithm, dynamically adjusting and optimizing model weights by federal reinforcement learning, and outputting threat vectors to a cloud causal engine; the method comprises the following steps: constructing a space-time causal diagram by combining threat intelligence, positioning root cause threats by applying a Do-Calculus algorithm, generating a dynamic defense strategy, optimizing access control by KL divergence constraint, locally encrypting and storing a strategy execution log, and generating an evaluation audit log. According to the method, the problems of insufficient cloud computing multi-modal data relevance, defense lagging and verification fault are solved, and collaborative crossing of evaluation precision and response efficiency is realized.

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.