360 results about "Proof of knowledge" patented technology

The invention discloses a collaborative sharing method, system and device on an energy data chain fusing multi-party security calculation and zero knowledge proof and a storage medium, and belongs to the field of energy data security sharing and block chain privacy protection, and the method comprises the steps: executing desensitization processing on original data according to types, and generating a cryptographic commitment value and a data hash identifier; encrypting and fragmenting the desensitized data, registering a task structure body through an intelligent contract, and uploading the task structure body; and each node decrypts the ciphertext, executes calculation and generates a zero-knowledge proof, and submits the zero-knowledge proof to the block chain to be verified by the smart contract. According to the method, data privacy protection and result verifiability unification are realized, cross-mechanism cooperation efficiency is improved, an auditing system on a whole process chain is constructed, and safe sharing of energy data is guaranteed.

A distributed intelligent authentication method based on dynamic multi-modal fusion relates to the field of network security, and adopts an alliance chain + DAG hybrid block chain architecture, combines a threshold signature to realize secret key fragment management, and switches among PBFT, Raft and probabilistic algorithms through a dynamic consensus mechanism to improve authentication efficiency. The multi-mode authentication module is based on a dynamic weight distribution algorithm, integrates biological characteristics, behavior analysis, equipment fingerprints and environmental factors, and combines an LSTM-GAN model and a quantum random number driven challenge-response mechanism to realize zero-trust verification under environmental perception. The session management module generates a session key by using a chaotic mapping algorithm. In the aspect of privacy protection, CKKS homomorphic encryption, zero-knowledge proof and attribute-based encryption are fused. According to the method, the block chain technology, the secure multi-party computing technology, the machine learning technology and the quantum cryptography technology are fused, and a high-performance, high-security and strong-privacy-protection distributed authentication solution is provided.

The invention discloses a financial data privacy protection system based on block chain security multi-party computing, and belongs to the technical field of data protection, and the system specifically comprises the steps that a data preprocessing module segments original financial data, and adds a unique watermark identifier; the distributed account book stores the Hash abstract and watermark mapping relation of the encrypted logic data fragment, and the digital signature and the timestamp are fused to ensure reliability; the computing node cluster receives data through a special interface, dynamically builds a computing group according to a service rule and outputs an encrypted computing result; bidirectional authentication is carried out on the zero-knowledge proof verifier and the computing node cluster to verify the data holding right; the encryption proxy gateway processes an output result of the computing node cluster to complete format conversion and ciphertext superposition; the cross-link routing module constructs a virtual coverage layer, cross-link transmission of encryption results is achieved through protocol conversion and three-way handshake verification, and a heterogeneous chain protocol converter and a verification assembly guarantee transmission safety; the financial data privacy security is comprehensively guaranteed, and the data processing efficiency and reliability are improved.

The invention provides an industrial Internet of Things security authentication method and system based on zero-knowledge proof, and relates to the technical field of security authentication, and the method comprises the steps: sending the identity information of terminal equipment to an authentication server through an edge computing node, generating an equipment certificate, and building an identity management information base; and the authentication server detects a computing resource occupancy rate of the terminal equipment according to the equipment authentication key, generates a zero-knowledge proof request, performs parallel verification, updates an equipment reputation score and predicts a next authentication session state. And selecting main and standby communication channels based on the prediction state, and triggering channel switching when the health degree is lower than a threshold value. And the authentication server determines a dynamic time slice allocation strategy according to the equipment reputation score, the service priority and the prediction state, and the edge computing node adaptively adjusts the size of the time slice to complete authentication request processing. According to the method, the authentication efficiency and security are improved, the computing resource consumption is reduced, and the system robustness is enhanced.

The invention relates to a gradient aggregation federated learning method based on combination of zero knowledge proof and a block chain technology, and belongs to the field of distributed machine learning. Through combination of zero knowledge proof (zk-SNARK) and an extensible block chain technology, limitations of a traditional method in aspects of data privacy protection and model verification are broken through. According to the method, the correctness of a global model is verified by using zero-knowledge proof, the transparency and data privacy of an aggregation process are ensured, the Chinese remainder theorem is introduced to compress the proof, and the storage burden of block chain nodes is reduced. And the hash value updated by the encryption model is recorded through the block chain, verification is carried out based on a block chain consensus node, and the data integrity and the system transparency are further improved. Besides, a dynamic client selection mechanism is introduced in the method, participants are optimized based on training performance scores, and the training efficiency and the model quality are improved. As a whole, the invention provides a safe, efficient and transparent distributed learning solution.

The invention relates to the technical field of blockchain privacy protection, and discloses a homomorphic encryption and blockchain privacy protection method and system, and aims to encrypt a transaction amount through multi-key fully homomorphic encryption, store transaction metadata in combination with a Hash commitment mechanism, ensure that data on a chain is always in an encrypted state, and prevent unauthorized access. And secondly, in order to solve the problem that the smart contract cannot directly process the ciphertext, homomorphic calculation is combined with zero-knowledge proof, so that the smart contract can verify the transaction legality under the condition of not decrypting data, and the calculation burden is reduced by combining multi-party calculation. And finally, in order to optimize the storage and query efficiency, in combination with under-chain encryption storage, the encryption hash value is only stored on the chain, and meanwhile, proxy homomorphic signature is adopted to enhance data access authority management, so that the expandability and calculation efficiency of the block chain are improved.

The invention relates to the technical field of textile informatization and block chain encryption traceability, in particular to a textile quality block chain encryption traceability method, which comprises the following steps of: implanting quantum dot-nucleic acid mixed fingerprints into yarns in a spinning stage and generating distributed identities; in the production link, process data are collected in a trusted execution environment, and are packaged into an encrypted packet by using homomorphic encryption, zero-knowledge proof and threshold signature; and after a batch threshold value is reached, calculating a batch commitment and a fragmentation commitment, fragmenting through erasure coding, writing the commitment and the proof into the directed acyclic graph according to a fixed field, and confirming through a Byzantine fault-tolerant consensus. Consumer off-line fingerprint comparison and homomorphic verification can realize authenticity identification, and after networking, batch certification is verified and credits are pledged. And when the time lock expires, the historical quality data is decrypted by multiple subjects in a combined manner, and maintenance suggestion hash is generated and written into subsequent transactions, closed-loop tracing from production to maintenance is realized, and anti-counterfeiting, privacy protection and quality improvement are realized at the same time.

The invention discloses a receiving information real-time synchronization and abnormity early warning method and system, and relates to the technical field of intelligent logistics information processing and data security, and the method comprises the steps: collecting logistics track data, constructing a space-time diagram model, and carrying out the track feature extraction through a space-time diagram convolution network; performing trajectory time sequence prediction by adopting a Transform model, and judging an abnormal event based on an abnormal detection threshold value; in combination with zero-knowledge proof and a block chain technology, encryption verification and evidence storage are performed on logistics data, and a logistics scheduling optimization and dynamic exception recovery strategy is constructed. According to the method, through space-time diagram modeling, ST-GCN trajectory feature extraction, Transform prediction analysis, block chain evidence storage and reinforcement learning scheduling optimization, a complete logistics information real-time synchronization and abnormity early warning system is constructed; by introducing the block chain and the ZKP technology, the integrity and privacy security of the data are guaranteed, and the risk of logistics fraud and information tampering is reduced.

The invention discloses a remote proving method for a trusted data space, which relates to the technical field of computer and data security, and comprises the following steps: initializing a trusted environment and generating a dynamic identity key for a heterogeneous terminal containing a CPU (Central Processing Unit), a GPU (Graphic Processing Unit) and an FPGA (Field Programmable Gate Array) based on a hardware security module and a physical unclonable function, and generating a challenge value by a verifier by using a quantum random number; the method comprises the following steps of: firstly, transmitting to a proving party through quantum encryption and a neuromorphic photonic network, constructing proving by the proving party by adopting a tensor decomposition zero-knowledge proving protocol, finishing multi-stage verification on a verification party in combination with a space-time cause and effect graph and quantum signature aggregation, and finally realizing dynamic trust evaluation and adaptive strategy adjustment through a quantum Bayesian network, reinforcement learning and biological feedback. According to the method, the remote attestation performance of the trusted data space is improved, dynamic trust evaluation is realized by means of the quantum Bayesian network and biological feedback, attacks are effectively resisted, real-time requirements are met, trust is accurately evaluated, and the development of the trusted data space is promoted.

The invention provides a motion data security management method and system in meta-universe smart motion, and relates to the technical field of meta-universe, and the method comprises the steps: obtaining user motion data and identity information, building an identity authentication model based on a zero-knowledge proof mechanism, generating Merkle tree zero-knowledge proof, and verifying the authenticity of the user identity. Carrying out distributed storage on the motion data by adopting a fragmentation storage technology; and providing corresponding data according to the access permission level of the third-party application. According to the invention, privacy protection and efficient storage of user data are realized, multi-level data access control is supported, and data security and utilization efficiency are improved.

The invention discloses a self-random cross-chain dynamic cooperative supervision method based on zero knowledge proof, which is used for realizing safe and supervisible privacy protection transactions in a block chain cross-chain environment. The method comprises the following steps: dynamically screening users through MACRO credit scores to form supervision chains, the number of which is consistent with that of application chains, and generating public and private keys; deploying a contract and a ZKP circuit in each chain, wherein ZKP generation adopts self-random hash; according to the supervision chain secret key and the self-random hash, the transaction is encrypted, verified and signed, and a random block header and a transaction link are recorded in a linker (TEE); after the supervision chain verifies the signature, the transaction is linked and stored in a supervision chain Merkel mountain range, and a linker is updated at the same time; a supervision chain of any party puts forward a supervision application, and after the supervision application is agreed by the opposite party, two rounds of two-layer secret sharing technology collaboratively supervise the recoverable transaction. According to the method, self-random encryption, zero-knowledge proof and dynamic supervision mechanisms are fused, and multi-key supervision, self-random encryption key dynamic change and multi-supervision-chain dynamic cooperative supervision are realized.

The invention discloses a multi-level access control and authority synchronization method for secure mobile storage, and belongs to the field of mobile storage security. Aiming at the problems of data leakage, poor authority management and the like of the mobile storage device, a multi-level access control framework, a decentralized authority synchronization mechanism and a dynamic token and zero-knowledge proof system are constructed. Generating a plurality of layers of sub-keys from a master key by using a PBKDF2 algorithm through hierarchical key generation, and associating different encryption areas and authority strategies; incremental synchronization is carried out based on a Merkle tree, and data consistency is guaranteed through a consistency verification protocol; a temporary token is generated by using a Schnorr protocol, and the permission is verified in combination with zero-knowledge proof, so that the privacy security is ensured. In scene application of a power grid and the like, a master key is activated through biological recognition, permission is loaded according to a strategy, and permission change is efficiently synchronized. According to the method, the mobile storage security and the management efficiency are improved, and accurate authority control and reliable synchronization are realized.

Systems and methods for performing zero knowledge proofs to prove a user's possession of secret data and / or biometric data without exposing such data. The methods can include receiving a certificate signing request and biometric data associated with a user; creating a stable key based at least in part on the biometric data; creating a private key based at least in part on the stable key; transmitting the private key to the user device for local storage thereon; creating a public key based at least in part on the private key; and forwarding the certificate signing request to an issuer.

The embodiment of the invention provides an enterprise credit data privacy protection method and device based on a zero-knowledge proof technology, and the method comprises the steps: obtaining enterprise credit data, and encrypting the data; adaptively selecting a zero-knowledge proof protocol according to service requirements; generating a pair of public key and private key, and selecting a zero-knowledge proof protocol to generate a zero-knowledge proof based on the private key and the enterprise credit data; transmitting the zero-knowledge proof and the public key thereof to a third party, so that the third party performs verification by using the received zero-knowledge proof and the public key; receiving a verification result fed back by the third party; through the zero-knowledge proof, the enterprise can prove the credit condition without disclosing specific credit data, so that sensitive information and commercial secrets are protected, the risk of data leakage is reduced, in addition, the enterprise does not need to share any sensitive data, does not need to decrypt and share the data, and can complete credit verification only by providing the zero-knowledge proof. And the potential risk caused by data sharing is greatly reduced.

The invention relates to a multi-participant longitudinal federated learning method based on data alignment and privacy protection, and belongs to the field of data security. According to the invention, by fusing security calculation of multi-party data, the requirements of data privacy protection and data collaboration are met, and meanwhile, the user is supported to solve the problems of data leakage and privacy invasion; according to the method, a safe multi-party data alignment mechanism is constructed in combination with zero-knowledge proof and homomorphic encryption technologies, data privacy is protected through an efficient encryption means, safe identification of common user data is achieved through multi-party private set intersection calculation, and the safety and efficiency of data collaboration are improved; according to the violation processing and reward and punishment mechanism, through supervision of a third-party review mechanism, it is ensured that the participants comply with protocol regulations in the data alignment and model training process, data abuse is prevented, and the protocol reliability and the compliance of the participants are enhanced.

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 provides a new energy income settlement data privacy protection method and device based on zero knowledge proof, relates to the technical field of block chain data security and cryptography, and solves the technical problems of sensitive data uplink privacy risk, settlement result multi-party verification and segmented electric quantity data privacy processing. The method comprises the steps of obtaining original new energy income settlement sensitive data, and performing preprocessing to obtain a Hash commitment value; constructing a zero-knowledge proof-circuit based on the Hash commitment value; generating a zero-knowledge proof pi by using the Hash commitment value and a zero-knowledge proof-circuit; and verifying the zero knowledge proof pi on the block chain to obtain a multi-party settlement verification result without leaking sensitive data. According to the method, multi-party credible verification of the settlement result is realized through a zero-knowledge proof technology on the premise that specific generating capacity and income values are not leaked, anti-quantum, multi-chain compatibility and ZK-Roollup optimization are integrated, and system safety and settlement efficiency are improved.

A privacy-preserving health verification system with incentive mechanisms for promoting regular testing behavior is disclosed. The system implements a cryptographic separation between user identity and verification status by extracting minimal verification metadata from health documentation and generating zero-knowledge proofs. Pseudonymous identifiers eliminate direct linkages between identity and health status while maintaining verification integrity. An algorithmic incentive mechanism analyzes temporal patterns between verification events, implementing streak detection with configurable grace periods and recovery acceleration factors. The system enables secure verification sharing with third parties through cryptographically signed, time-limited tokens containing no personally identifiable information. The implementation simultaneously solves privacy challenges and psychological barriers to regular testing, delivering a viable solution for improved testing schedules and enhanced compliance with recommended health protocols, particularly in sensitive health domains such as sexually transmitted diseases and infections.

The invention discloses a financial transaction data intelligent protection method and system based on a block chain, and belongs to the technical field of block chains, and the method comprises the steps: collecting financial transaction data from a data source of a financial transaction system, and carrying out the cleaning, format unification and abnormal value detection processing; dynamic encryption strength adjustment is carried out through the smart contract according to the sensitivity and the purpose of the transaction data, compared with a traditional fixed encryption mode, data can be protected more accurately, identity authentication is carried out in combination with a zero-knowledge proof mechanism, specific identity information does not need to be exposed in the identity authentication process, identity information leakage is effectively prevented, and user experience is improved. Encrypted financial transaction data are recorded in a block chain, it is ensured that the data are not maliciously tampered in the storage and transmission process through the non-tampering characteristic of the block chain, each transaction generates a unique hash value as an identity identifier, and decentralized propagation and consensus verification are performed in a block chain network, so that the security of the transaction is improved. And the integrity and credibility of the data are further enhanced.

The invention relates to the technical field of data security, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a decentralized identity verification method, device, equipment and medium, comprising: generating an asymmetric key pair, generating a decentralized identifier based on a public key and recording the decentralized identifier to a distributed account book, a verifiable certificate containing a declaration is generated by a certificate issuer and signed, a verifiable demonstration satisfying a verification challenge is generated by using a zero-knowledge proof module in response to a verification request, and the verifiable demonstration is signed by using a private key to obtain a signed verifiable demonstration. And sending the signed verifiable demonstration to the verifier, querying the public key verification signature of the voucher issuer and the user side from the distributed account book through the smart contract, and outputting a verification result. According to the invention, the identity verification is realized through the combination of the distributed account book, the zero-knowledge proof and the smart contract, the direct exposure of sensitive information is avoided, and the safety and interoperability of cross-platform identity verification are improved.

In a blockchain, transacting a record comprises performing linear network coding on the record or on a data file corresponding to the record, to produce a plurality of coded data parts; and storing at least one of the plurality of coded data parts on the blockchain or storing a proof of knowledge on the blockchain, the proof of knowledge derived from the coded data parts. Linear network coding coefficients might be derived from cryptographic hashes of the plurality of coded data parts. An all-or-nothing transform can use the cryptographic hashes to provide the proof of knowledge.

The invention discloses a zero-knowledge proof generation method and device, equipment and a storage medium, and belongs to the field of data security. The method is applied to a management platform, the management platform is used for managing an infrastructure, the infrastructure comprises a plurality of computing resources, and each computing resource is used for generating ZKPs corresponding to various attestation protocols. The method comprises the steps that a proof generation request is received, the proof generation request comprises proof protocol information and a circuit file, the proof protocol information is used for indicating a target proof protocol used for generating a target ZKP, the target proof protocol is one of the multiple proof protocols, and the circuit file is used for indicating a calculation model for generating the target ZKP; determining a target computing resource from the plurality of computing resources according to the proof generation request; and generating a target ZKP through the target computing resource. According to the method, the ZKP can be generated by adopting different ZKP protocol types.

The invention discloses a verifiable privacy information retrieval mechanism based on homomorphic encryption. The method comprises the following steps: S1, after initialization is completed, a data owner generates a zero-knowledge proof while constructing a private information retrieval challenge, proves that a challenge structure is legal, and submits the proof to a trusted third party (TTP); s2, the server receives the inquiry verified by the TTP and then performs homomorphic calculation, generates an encrypted response and sends the result to the data owner and the TTP, and the TTP synchronously records response information; s3, the data owner carries out decryption and Hash comparison on a returned result, if an exception is found, an objection request can be submitted, and verification is carried out by the TTP in combination with challenge and response zero-knowledge proof; and S4, arbitration and responsibility tracing: the TTP judges the dispute based on a verification result, and determines a responsibility party. The method is suitable for private information retrieval scenes with high requirements on data security and integrity.

The invention belongs to the crossing field of medical information technology and privacy calculation, and particularly relates to a medical privacy protection method based on zero-knowledge deep learning, which comprises the following steps: constructing a medical privacy protection system comprising a client and a doctor side, and deploying a zero-knowledge neural network model based on an improved zkReLU activation function at the doctor side; the patient end receives physiological data input by a patient, carries out sensitivity grading on the physiological data, and encrypts the physiological data with different sensitivities by adopting different algorithms to obtain encrypted data; inputting the encrypted data into a zero-knowledge neural network model for forward propagation to obtain a middle-layer zero-knowledge proof; the patient terminal initiates a diagnosis result query request, and the doctor terminal integrates the intermediate layer zero-knowledge proof to generate an aggregate zero-knowledge proof to wait for verification; the verifier verifies the correctness of the aggregated zero-knowledge proof through the verification public key, and confirms that the diagnosis result accords with a preset rule and the irrelevant privacy of the patient is not leaked; local decryption of high-sensitivity data and encryption reasoning of low-sensitivity data are realized, and the leakage risk is eliminated.

A method of enabling knowledge proof in a blockchain transaction is disclosed. The method comprises sending, from a verifier to a prover, a blockchain transaction redeemable by means of data including (i) first data (y) based on a combination of an ephemeral key (r), second data (c) and a private key of a public-private key pair of a cryptography system, wherein the public key (v) is based on an integer generator raised to a first power, wherein the first power is based on the private key, and wherein knowledge of the private key is required in order to determine the ephemeral key from the first data, and (ii) third data (x) based on the integer generator raised to a second power, wherein the second power is based on the ephemeral key.

The invention discloses a distributed key generation method and device based on an SM2 algorithm, a medium and equipment. The method comprises the following steps: determining a class group encryption key, a class group decryption key and a corresponding first zero knowledge proof through public parameters generated based on the SM2 distributed key; each participant shares respective secret share based on the class group encryption key, the class group decryption key and the first zero-knowledge proof, and creates a second zero-knowledge proof indicating that sharing is correct; each parameter party collects honest distribution shares and decryption shares based on the second zero knowledge proof, calculates a part of private keys and a part of public keys according to the decrypted secret shares, and creates a third zero knowledge proof indicating correct decryption; according to the third zero knowledge proof, partial public keys of participants correctly executing decryption operation are determined to reconstruct a global public key, the secret is shared by using a polynomial, each participant can contribute a part of shares, and a distributed secret key is generated without any credible setting.

The invention discloses a multi-dimensional credit asset traceability system and method. The system comprises a data acquisition and encryption module (10) which is used for performing encryption and digital signature on credit asset data based on a trusted execution environment (TEE) and a hardware security module (HSM) at a data generation end; the parallel Hash processing module (20) is used for performing parallel Hash operation on the encrypted data and generating leaf node Hash values based on GPU acceleration and a multi-thread technology; the nested hash and zero-knowledge proof module (30) constructs leaf node hash values into a compression type Merkle tree and generates a zero-knowledge proof (ZKP), so that a third party can verify the authenticity and consistency of data without accessing full data; the on-chain evidence storage module (40) is used for recording root Hash (RootHash) and zero knowledge proof of the compression type Merkle tree to the block chain; the dynamic authorization and secure multi-party computing module (50) performs access clipping on the credit asset data based on the access intention and realizes verification of the minimum data dimension through secure multi-party computing (SMPC). Through combination of technical means such as trusted hardware acquisition, parallel hash calculation and privacy protection verification, rapid verification is realized on the premise of not exposing original data, and verification performance, data security and privacy protection capability are remarkably improved.

The invention provides a multi-tenant multi-user login method based on enhanced OAuth2, which relates to the technical field of network security, and comprises the following steps: obtaining a key threshold through a tenant identifier, and executing OAuth2 authentication to obtain an access token; tenant fingerprint information is generated through zero-knowledge proof and homomorphic encryption, and a tenant verification token is generated through secure multi-party calculation; constructing a reinforcement learning access controller in combination with the historical access data, and generating and verifying an authority list; and finally forming a session identifier and storing the session identifier in a distributed cache. According to the invention, the authentication security is improved, cross-tenant fine-grained authority management is realized, and unauthorized access is effectively prevented.

The invention relates to the technical field of block chain technology and artificial intelligence collaboration, and discloses a verifiable multi-agent collaboration method based on smart contract driving, comprising the following steps: task planning generates a directed acyclic graph and a zero-knowledge proof circuit template, submits the directed acyclic graph and the zero-knowledge proof circuit template to a planning contract, and deploys an exclusive zero-knowledge proof contract; the AI agent collaboratively executes the subtasks, and zero-knowledge proof is generated and submitted through a Veckrii auction tool; zero-knowledge proof contract chain verification is carried out, and after verification is passed, a signature is received and multi-layer gating verification is executed; and the governance contract carries out pledge management and cost distribution on the agents, the providers and the experts. According to the method, zero-knowledge proof and a trusted execution environment are combined, and an under-chain execution behavior is converted into an encryption certificate capable of being verified on a chain, so that the problem that the execution process cannot be verified due to the lack of distributed trusted evidence storage in a traditional centralized framework is effectively solved; and after each subtask is completed, double signature and multi-layer gating verification are forcibly executed.

The invention relates to the technical field of communication security, discloses a cross-domain authentication method based on zero-knowledge proof, and aims to improve security and privacy protection in a cross-domain authentication process. According to the method, the advanced zero-knowledge certification technology is used, the user is allowed to certify the certification qualification of the user to the certification server or the service provider under the condition that no personal sensitive information is leaked, the Groth16 zero-knowledge certification protocol is adopted, efficient, safe and anonymous cross-domain certification is achieved, and the method is suitable for application scenes needing high privacy protection and safety.