661 results about "Zero-knowledge proof" patented technology

A computer-implemented method and system for privacy-preserving location verification in distributed networks comprises initializing a multi-modal biometric authentication system on a user device, generating cryptographic keys using a distributed key generation protocol, binding the cryptographic keys to biometric templates using a fuzzy vault scheme, constructing and broadcasting encrypted location beacons, and generating zero-knowledge proofs of location claims. The system includes user devices equipped with biometric sensors and verifier devices configured to validate location claims and maintain consensus in a blockchain network. The method implements real-time liveness detection for multiple biometric input types, executes fault-tolerant consensus algorithms with privacy preservation, and maintains a dual-scoring mechanism comprising device trust scores and user reputation scores. The system enables secure location verification while preserving user privacy through cryptographic protocols and biometric authentication in decentralized environments.

The invention discloses a financial data risk control system and method based on big data, and relates to the technical field of financial science and technology, and the system comprises a multi-source data collection module which achieves cross-mechanism safety collection through federal learning; the data cleaning and preprocessing module is used for processing abnormal values and missing values by using an improved algorithm; the knowledge graph construction module is used for constructing a dynamic knowledge network based on an innovative algorithm; the risk assessment engine fuses various models to assess risks; the real-time monitoring and early warning module is used for realizing second-level response by utilizing multi-scale analysis; the decision support module is used for optimizing a strategy based on reinforcement learning; and the audit tracking module guarantees evidence storage and privacy through zero-knowledge proof, and all the modules cooperate to improve the risk control capability. According to the financial data risk control system and method, risks are accurately recognized, real-time monitoring and early warning are achieved, data security sharing is achieved, risk control strategies are dynamically optimized, risks and business development are balanced, the risk prevention and control capacity and economic benefits of financial institutions are improved, and data privacy and risk control transparency are guaranteed.

The invention discloses a digital asset secure transaction system and method based on a block chain, and belongs to the cross field of block chain technology and financial science and technology. The system adopts a layered architecture design and comprises an intelligent contract execution layer, a distributed account book storage layer and a cross-chain interaction layer. The transaction method comprises the following steps: generating a digital identity certificate based on asymmetric encryption, and realizing privacy protection through zero-knowledge proof; a secure transaction channel is constructed by adopting a multi-signature mechanism, and sensitive data processing is performed in combination with a trusted execution environment; and designing a dynamic fragmentation strategy to optimize the transaction throughput, and establishing an on-chain and off-chain collaborative verification mechanism. The innovation point is that a double-layer verification model combining a verifiable delay function and a threshold signature is provided, and millisecond-level confirmation is realized while the transaction irreversibility is ensured. The system supports multi-chain asset atomic exchange, and interoperability of different block chain networks is realized through a heterogeneous cross-chain gateway. The scheme has the characteristics of high transaction confirmation speed, high privacy protection level and high system expansibility.

The invention discloses an intelligent management method and system for port and navigation Internet of Things data, and the method comprises the steps: generating a standardized data flow through a multi-modal data fusion model according to the heterogeneous features of ship navigation data, port equipment operation data and cargo information; generating an anti-interference transmission channel based on the standardized data stream; according to the real-time data received by the anti-interference transmission channel, dynamically generating a tamper-proof storage index through a trusted execution environment; extracting multi-source data based on the storage index, and generating a ship arrival time prediction model and a port resource scheduling strategy; and according to the port resource scheduling strategy, constructing a cross-department data sharing network through a federated learning framework and a zero-knowledge proof protocol, and generating a verifiable shared data set. According to the embodiment of the invention, port and navigation Internet of Things data management with reliable transmission, safe storage and collaborative intelligence can be realized, and the data management efficiency is improved.

Systems, methods, and / or computer readable storage media for protecting data. A system can include one or more processing circuits configured to receive or identify at least one token including cyber resilience data of at least one entity and corresponding with at least one posture or compliance parameter of at least one third party The one or more processing circuits can perform a zero-knowledge proof (ZKP) on the cyber resilience data, determine at least one posture or compliance parameter of the at least one third party is satisfied based on the cyber resilience data, and / or generate at least one ZKP including at least one cryptographic commitment obfuscating the cyber resilience data. The one or more processing circuits can provide, to at least one third party computing system of the at least one third party, the at least one ZKP or indication of performance of the at least one ZKP.

The invention discloses an industrial equipment fault prediction system based on federated learning and a privacy protection method, and relates to the field of industrial equipment fault prediction. The data acquisition preprocessing module extracts fault features through compressed sensing downsampling, screens and uploads the fault features; the federal learning training module adopts a layered architecture and a dynamic algorithm to schedule a learning rate; the fault prediction and diagnosis module constructs a space-time diagram neural network and fuses a physical model to improve generalization; the privacy protection security communication module performs homomorphic encryption storage and zero-knowledge proof verification update; the knowledge graph construction reasoning module constructs a dynamic graph, locates a fault root cause through causal reasoning, and supports cross-device knowledge migration. By adopting the quantum and federated learning technology, the industrial equipment fault diagnosis accuracy is high, the attack resistance is high, the encryption efficiency is greatly improved, the model training time is shortened, cross-equipment knowledge migration is realized, the operation and maintenance cost is reduced, and the intelligent operation and maintenance development of the industrial equipment is promoted.

The invention relates to the technical field of traffic data processing, and discloses a traffic edge computing data security sharing method and system, and the method comprises the steps: collecting traffic edge computing network multi-source heterogeneous data, and carrying out the classification standardization processing to generate a structured data set; designing a dynamic data sharing security protocol based on a multi-party security computing protocol and a homomorphic encryption algorithm; verifying the authority of a requester in a multi-level manner by using an attribute-based access control model and a zero-knowledge proof mechanism, and generating a dynamic access token; storing data by adopting a fragmentation storage and redundancy encryption strategy, and recording storage information through a hash chain; and dynamically adjusting the encryption strength and the sharing strategy according to the network threat level and the data sensitivity. The method effectively guarantees safe sharing of traffic data, accurately controls access authority, improves storage and sharing efficiency, adapts to complex network environment changes, and provides powerful support for development of an intelligent traffic system.

The invention discloses an electronic seal management and control method and system, and belongs to the technical field of electronic seal management, and the method comprises the steps: carrying out the identity verification of a seal use request; dividing a private key of the electronic seal into a plurality of key shares; a digital signature of the electronic seal is generated through cooperative calculation of a threshold signature mechanism; managing electronic seal key access in a trusted execution environment, and executing global signature calculation in a hardware encryption module; adopting a zero-knowledge proof algorithm to generate verifiable calculation proof data in the digital signature calculation process; and establishing a quantum communication link and generating a transmission key, and managing key transmission. According to the invention, the distributed storage private key is calculated through multi-party security, so that the risk of single-point leakage is eliminated; zero-knowledge proof is adopted to ensure that signature calculation is verifiable, and signature credibility is improved; secret key access is dynamically managed and controlled based on the trusted execution environment, and safety and flexibility are enhanced; quantum key distribution is utilized to ensure key transmission safety, and quantum attacks are resisted.

A decentralized artificial intelligence platform is disclosed that enables secure sharing and execution of AI modules in sensitive application domains. The platform comprises a knowledge module registry for discovering specialized AI modules, a security framework enforcing structural integrity of AI modules, a zero-knowledge proof validation service for verifying usage conditions without exposing private data, and a blockchain-based value chain for managing smart contracts and payments. In operation, an AI agent can fetch a required AI module from the knowledge module registry, prove the right to use it, execute the AI module on local data, and automatically pay the AI module's provider through a blockchain transaction.

The invention discloses a large model generation content traceability technology based on model copyright ID watermark embedding, which comprises the following steps that: firstly, a large model content generator compiles a dynamic watermark embedding process into an arithmetic circuit, and generates a watermark text and a proof by using a zero-knowledge proof algorithm; then the large model content generator publishes the text with the watermark and the proof together, and hides the copyright ID and the secret key; a large model content user verifies the proof and the watermarked text through a smart contract by adopting a zero-knowledge verification algorithm; after verification is passed, an adversarial sample corresponding to the text with the watermark is generated, an adversarial training method is used for optimizing the text with the watermark, and parameters of the Viterbi balance algorithm are dynamically adjusted and improved. According to the method, the concealment and the generation quality are balanced, high-capacity watermark embedding is realized, the tamper resistance and the accurate traceability of multi-model copyright disputes are improved, and the privacy protection intensity is improved.

The invention provides a multilevel dynamic authorization and access control method and system based on an identity token, and relates to the technical field of network security, and the method comprises the steps: generating a user main token of a binding terminal, constructing a resource access domain knowledge graph, carrying out the feature coding, predicting an access intention based on knowledge enhancement features and user historical behaviors, and achieving the dynamic grouping of resources. A permission certificate is generated through homomorphic encryption, verifiability is ensured through zero-knowledge proof, a verification program is deployed in a distributed network, and collaborative detection and certificate revocation of abnormal access are achieved. According to the invention, the security and flexibility of access control are improved, and the dynamic adaptive capacity of authority management is enhanced.

The invention provides a government affair cloud cross-department data security sharing method and device, and relates to the technical field of data security. The method comprises the following steps: a main chain of a block chain performs first-level verification on a requester based on a VerifyCredate contract and an access policy white list set by a department to which government affair data belongs; the access strategy is a dynamic attribute base access strategy generated by a department to which the government affair data belongs based on a dynamic attribute encryption technology; under the condition that the first-level verification is passed, generating an access credential, synchronizing the access credential to a side chain of the block chain, generating a zero-knowledge proof by the side chain according to the operation log, and initiating a zero-knowledge proof verification request to the main chain to perform second-level verification; and under the condition that the main chain passes the second-level verification, determining a cross-domain trust score between the government affair data requesting department and the department to which the government affair data belongs based on the digital certificate submitted by the requester by adopting a federal model, and performing third-level verification according to the cross-domain trust score. According to the invention, the data sharing security can be improved.

The invention discloses a data ownership verification and authorization control method based on zero knowledge proof. The method comprises the following steps: constructing a traceable Merk tree structure on a block chain or a distributed account book; a data owner calculates data fingerprints and packages the data fingerprints into declaration nodes to be inserted into the traceable Merk tree; storing the ownership zero knowledge proof and the traceable Merk tree root hash into a block chain together; the verification party executes the zero-knowledge verifier contract on the chain to complete ownership verification without reading original data or identity plaintext; access control is realized after on-chain verification of the service party; triggering local heavy hash to update the traceable Merk tree root hash, and broadcasting a revocation event on a chain; and confirming legality of evolution and authorization change of all nodes. According to the method, the historical traceability and structural consistency of the data ownership and authorization relationship are ensured, and efficient traceability and anomaly detection of the node evolution chain are also realized.

The invention relates to the technical field of block chains, and discloses a distributed data security storage system and method based on a block chain, and the system comprises a dynamic fragmentation encryption module which can automatically select a fragmentation strategy based on a data sensitivity level; the data sensitivity is set to be S, the data sensitivity level is determined through the following formula: # imgabs0 #, wi is the weight of the ith factor influencing the data sensitivity, fi (D) is the quantized value of the data D under the ith factor, and for low-sensitivity data (S is smaller than or equal to Slow, and Slow is a preset low-sensitivity threshold), ECIES asymmetric encryption and random fragmentation storage are adopted; and high and low sensitive data. Through the dynamic fragmentation encryption module, hierarchical storage and flexible encryption of data are realized, and storage redundancy is reduced; the cross-chain verification engine adopts zero-knowledge proof, and cross-chain verification is safely and efficiently completed; the storage node reputation system is combined with LSTM to predict the node failure probability, and reliable data storage is guaranteed; all work processes are tightly matched, and the whole process ensures data safety and efficient circulation and management.

The invention relates to the technical field of big data, and discloses a resource pool planning method based on a computing power network, comprising the following steps: S1, global resource modeling; s2, intention-driven resource slicing; s3, intelligent scheduling and load balancing; s4, predictive fault-tolerant self-healing is carried out; s5, energy efficiency optimization resource recovery; according to the method, a safe and efficient distributed computing power network resource awareness framework is constructed by fusing a dynamic key agreement protocol and a federated learning mechanism; according to the new method, the resource discovery accuracy, the state updating timeliness and the abnormal node recognition capability are remarkably improved, and meanwhile, the privacy leakage risk in cross-domain collaboration is effectively avoided through the national secret algorithm encryption, block chain auditing and zero-knowledge certification technologies; according to the method, greenization and high efficiency of resource allocation are realized through a carbon perception dynamic scheduling strategy and a multi-objective optimization model; tasks are preferentially scheduled to green energy nodes, energy consumption of idle nodes is reduced in combination with a dynamic frequency modulation technology, and system energy consumption and carbon emission are reduced.

The invention relates to a cross-domain authentication method based on a block chain, and the method comprises the steps: obtaining distributed identity data, carrying out the coding through employing a preset hash function, and obtaining a coded identity; recording an identity verification log based on the encoded identity label, and retrieving label consistency data from an account book according to the verification request to obtain a legality verification result; obtaining a dynamic permission allocation strategy through a legality verification result, generating a temporary access credential meeting the access requirement, and determining the content of the dynamic credential; extracting a permission range based on the dynamic voucher content, encrypting the permission range by adopting a zero-knowledge proof protocol, acquiring proof data, distributing the proof data to a cross-domain access target domain, and if the target domain feeds back a verification request, checking credibility according to the proof data, and obtaining an access permission validity result, extracting an access demand matching degree for comparison verification, and determining a cross-domain access passing state. According to the method, the trusted identity management requirement in a complex heterogeneous network environment can be met.

The invention provides a data traceability verification method in a trusted data space, and relates to the technical field of zero-knowledge certification, the method comprises the following steps: collecting a plurality of operation records of target data in the trusted data space, and arranging the operation records according to a timestamp sequence to generate an operation sequence; converting into a state transition constraint condition; inputting the operation sequence into a pre-trained key node identification model, and outputting position identifiers of one or more key state transition nodes in the operation sequence; constructing a zero-knowledge proof circuit according to the operation sequence, the state transition constraint condition and the key state transition node, and operating the zero-knowledge proof circuit to generate a composite zero-knowledge proof; and providing the composite zero-knowledge proof as a data traceability voucher of the target data to a verification party to complete traceability verification of the whole processing process of the target data. The technical problems of privacy disclosure risk and low verification efficiency of data traceability verification in the prior art are solved.

Embodiments are directed toward a blockchain system including a global state and an assemblage of blocks, each block representing a collection of state transformation records, each state transformation record describing a state transformation performed on the global state, where preceding blocks referenced by any given block contain state transformation records describing state transformations performed on the global state prior to the evaluation of the given block, and where at least one state transformation record is a zero-knowledge transformation record encoding a zero-knowledge state transformation description, which zero-knowledge transformation record comprises at least the following elements: paths identifying the locations of the elements of a discrete data subset, a revised data subset, and a transition proof implemented as a non-interactive zero-knowledge proof, which transition proof proves that the transition from the discrete data subset to the revised data subset follows the established rules of the blockchain system.

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 an enterprise-level cloud computing resource dynamic allocation and management system and an implementation method thereof, and relates to the technical field of computing resource management. According to the invention, cloud resource use data is collected and processed in real time through the resource state sensing and preprocessing module, and a load change rule is accurately extracted in combination with the load analysis and period detection module, so that intelligence and adaptive adjustment of resource allocation are realized, and the resource utilization efficiency and the service response speed are remarkably improved; meanwhile, by recording an operation log, generating a trust certificate and dynamically adjusting the access authority, the credibility and transparency of the resource allocation process are enhanced by using a block chain technology and a zero-knowledge proof protocol, and data tampering and trust crisis are effectively prevented.

The invention discloses a stable transmission method for server data encryption and rapid authentication, and belongs to the technical field of data security. The method comprises the following steps: dividing data into three levels of core sensitive data, important data and common data by utilizing a semantic analysis model; performing encryption protection on different levels of data by adopting a hierarchical encryption strategy; a master key is generated based on a chaotic system, a session key is generated in combination with a timestamp and a device fingerprint and is regularly alternated, and secure distribution is performed through a trusted execution environment and a block chain; multi-modal features are fused, the identity is verified through zero-knowledge proof, and the authentication strength is adjusted through dynamic risk assessment. The method is suitable for cloud computing, the Internet of Things and a distributed storage system, through deep fusion of a multi-level hybrid encryption algorithm, a dynamic key management mechanism and a self-adaptive authentication strategy, data security encryption, rapid authentication and stable transmission are achieved, and security, efficiency and adaptability are improved.

The invention discloses a data circulation trusted system and device based on a block chain and privacy calculation, and relates to the technical field of trusted data. Comprising a data supply end, a data demand end and a credible supervision end, the data supply end comprises a digital identity identification module which is used for generating a dynamic digital identity according to an enterprise unified social credit code and an ISO industry classification code and submitting the dynamic digital identity to a first block chain of the credible supervision end for authentication; the mixed desensitization module is used for carrying out first 3-bit plaintext reservation and hash replacement on the sensitive field by adopting an AES-256 algorithm, binding a UTC timestamp to generate a desensitization record and uploading the desensitization record to a first block chain; and the zero-knowledge proof generation module is used for converting the privacy calculation result into a zero-knowledge proof voucher and pushing verification parameters to a sandbox environment of the data demand end. According to the invention, the security and privacy of data in a circulation link and the credibility of transactions are guaranteed, and the problems of privacy leakage, uncredible transactions, difficult supervision and the like possibly existing in data circulation are solved.

The invention provides a medical data sharing method and system based on multi-party security computing, and the method comprises the steps: carrying out the credible access control of participants through zero-knowledge proof and biological feature authentication, and enabling the participants to comprise a medical institution, a medicine enterprise / research institution, a patient and a supervision institution; after credible access control is passed, when a medical institution extracts patient data, k-anonymity, differential privacy and homomorphic encryption technologies are utilized to encrypt and desensitize the extracted patient data and store the data to a block chain; receiving a calculation task request and calculation parameters published on the block chain by a medicine enterprise / research institution, realizing mixed circuit and secret sharing mixed multi-party security calculation by a calculation node based on an ABY3 framework, and verifying the compliance of a calculation result; and receiving a result verification and auditing request of the supervision mechanism, and if the calculation result is verified to be within an authorization range through the smart contract, allocating rewards to the medical mechanism, the calculation node and the block chain platform according to a preset proportion, thereby effectively improving the security and timeliness of medical data sharing.

The invention relates to the technical field of data cross-domain access control, in particular to a block chain-based trusted data space cross-domain access control method, system and device and a medium, comprising: receiving a data access request, and analyzing a target data identifier, a target heterogeneous system identifier and access scene information; obtaining the data attribute of the target data according to the target data identifier, generating a dynamic access strategy in combination with the access scene information, and deploying the dynamic access strategy into the block chain; mapping the dynamic access strategy into an equivalent access control rule, and converting the data access request into target compatible request data; verifying zero-knowledge proof provided by the user based on an equivalent access control rule and a user public key; after the verification is passed, routing the target compatible request data to the target heterogeneous system; and the target heterogeneous system generates original response data, converts the original response data into user-side compatible response data and returns the user-side compatible response data to the user. According to the invention, cross-system efficient cooperation is realized, and the real-time adaptability and privacy enhancement security of access control can be improved.

The invention relates to the field of block chain technology and application security, and discloses a block chain-based APP data trusted storage and sharing method, which comprises the following steps of: maintaining a verifiable state container comprising state data and an access policy dual-Merkel tree under a chain, and recording a root hash of the verifiable state container in the block chain; for different updates, generating corresponding evidences: generating single-step evidences containing Merkel evidences for single-step updates; and generating the composite proof containing the zero-knowledge proof for the complex process. And the intelligent contract can update the root hash in an atomized manner only through verification and certification. During data sharing, data and dual Merkel proof are provided for a consumer to verify data authenticity and access legality. According to the method, complex calculation is arranged under a chain, low cost and constant overhead of on-chain verification are achieved, and meanwhile high-safety data credible storage and refined authority control capacity are provided through a dual-tree dual-certificate mechanism.

The invention relates to the technical field of communication network security, and particularly discloses a distributed communication network security verification method and system, which comprises a two-factor identity authentication module, a dynamic key arrangement and encryption module and a cross-node integrity verification module, and the dynamic key arrangement is respectively connected with the two-factor identity authentication module, the encryption module and the cross-node integrity verification module. Through combination of biological feature anchoring and secure multi-party calculation, on the premise of protecting privacy of original biological data, deep binding of biological features and public keys is realized, and biological uniqueness is given to identity authentication; and dynamic authentication interaction is fused with a timestamp, a biological characteristic entropy value and zero knowledge proof, replay attacks are resisted, 'human-equipment-identity 'consistency is accurately verified, a public key fragment is updated after authentication is passed, an identity trust chain is continuously reinforced, and it is ensured that node identities are true and credible from the source.

The invention provides a credible identity authentication method and system with privacy protection and traceability, and the method comprises the steps: S1, defining roles in an identity authentication process and a supervision traceability process and the function division of each role, including a user, a registration organization RA, a certificate issuer Issuer, a service provider SP and a supervision committee RegComm; s2, realizing an identity authentication process through a real name authentication verification process, an anonymous identity certificate signing and issuing process and a user identity authentication proving process; wherein in the anonymous identity certificate issuing process, a certificate issuer Issuer issues a verifiable anonymous identity certificate to a user through a formula according to a real name authentication verification result of a registration authority RA; and S3, realizing a supervision and tracing process through user secret distribution and a user information tracing process. According to the invention, an identity authentication process based on zero-knowledge proof and verifiable secret sharing is realized, a supervision and tracing process is introduced, and practical application requirements of privacy protection and traceability can be met at the same time.

The invention relates to the technical field of data processing, and discloses a distributed trusted data space construction method and system based on a block chain, and the method comprises the steps: enabling a participant to complete registration under a unique identifier of a data space through a digital identity certificate; dynamically creating a fragment block chain of the data space according to the unique identifier; the participant encrypts structured data and stores the encrypted structured data to the corresponding fragmented block chain to obtain a data block of the structured data; when a data interaction request of the cross-fragment block chain appears, generating a cross-chain verification certificate of the cross-fragment block chain based on zero-knowledge proof; data interaction of the fragmented block chain is completed through the cross-chain verification certificate, and an interaction audit record of the data interaction is generated; periodically aggregating the state hash of the fragmented block chain, and updating the global state snapshot under the unique identifier; according to the invention, the security of the trusted data space can be improved.

The invention provides a multi-level architecture-based cross-chain communication and privacy protection method, system and device, and a storage medium, and relates to the technical field of data processing, and the method comprises the steps that an application layer receives a cross-chain asset exchange request initiated by a user through a first block chain network, the request comprises source chain asset information, target chain asset information and a user identity identifier; the application layer executes KYC anti-money laundering verification based on the user identity identifier, and verifies whether a source chain asset address exists in a preset blacklist, so as to obtain a compliance verification passing result; and the protocol layer generates a cross-chain transaction proposal in response to a compliance verification passing result, and constructs a verifiable proof based on a zero-knowledge proof technology. According to the method, the natural contradiction between privacy protection and supervision compliance in a block chain cross-chain scene is solved.

The invention relates to the technical field of automatic driving, in particular to an automatic driving system based on intelligent traffic, which comprises a multi-source heterogeneous sensing fusion unit, a group collaborative decision-making unit and a dynamic control optimization unit, the group collaborative decision-making unit carries out space-time alignment on multi-source heterogeneous data, constructs and updates a global environment perception knowledge graph, carries out modeling on vehicle trajectories based on a Monte Carlo tree search framework in combination with deep reinforcement learning and risk perception, and trains a deep Q network model by adopting federated learning and adversarial training. A traffic flow distribution scheme is generated by applying multi-agent deep reinforcement learning and a game theory, storage data is proved by using homomorphic encryption and zero knowledge, a dynamic control optimization unit predicts, controls and plans an acceleration curve through a nonlinear model, and a transverse path tracking error is controlled by fusing sliding mode control and a fuzzy logic algorithm. And the safety of automatic driving is improved.