822 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 relates to the technical field of medical terminal data secure transmission and real-time management and control, in particular to a bank medical intelligent terminal data secure transmission and real-time management and control system and method. The behavior analysis module is used for calculating threat indexes through federated learning, the strategy module is used for dynamically switching algorithms and isolating anomalies, and the audit module is used for block chain verification and zero knowledge verification to generate a report. According to the method, dynamic encryption and fragmentation cutting are driven through sensitivity grading labels, the accuracy of data protection is improved, a time sequence attack path is blocked based on cooperation of fragmentation time sequence reference and an encryption transmission protocol, and dual guarantee of decentralized auditing and tampering positioning is realized by combining block chain hash identification and zero-knowledge proof verification, so that the security of data protection is improved. And full-link safe transmission and real-time management and control requirements of medical terminal data are met.

The invention discloses an artificial intelligence data privacy protection system based on a block chain and federated learning, and relates to the technical field of block chains and federated learning, and the system comprises a block chain module which employs a main chain-side chain double-chain architecture, a main chain stores a global model hash value and node reputation evaluation data, and a side chain module is used for storing node reputation evaluation data; the side chain stores the encrypted local model parameters through a fragmentation technology; the federated learning module comprises a dynamic difference privacy algorithm and a gradient ternary processing unit, and is used for adding noise to the gradient in a local training stage and converting the gradient into a ternary numerical format; the privacy protection module is used for integrating homomorphic encryption and zero-knowledge proof technologies and realizing ciphertext aggregation and verification of model parameters; and the malicious node detection module is used for identifying abnormal gradient update based on cosine similarity and Multi-Krum algorithm, and is linked with node reputation data in the block chain module. Through a system architecture and a privacy protection mechanism, the efficiency and performance of federal learning are improved while data privacy is ensured, and the method has a wide application prospect.

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 data security and privacy management method and system based on a block chain technology, and the method comprises the following steps: S1, collecting original data in a target system, and carrying out the preprocessing of the original data; s2, constructing an access control strategy set; s3, converting into a structured strategy configuration file, and deploying a smart contract; s4, matching and judging the access request and a preset strategy by the intelligent contract; s5, judging whether the access request is legal or not; s6, performing structured processing on the access log, and writing the access log into a block chain account book; s7, intelligently selecting an encryption mechanism, and providing access return data to the access party; and S8, carrying out modeling prediction on the access mode by adopting a federal gradient lifting tree algorithm. The block chain intelligent contract and the federal gradient boosting tree algorithm are fused, differential privacy, zero-knowledge proof and homomorphic encryption technologies are combined, data intelligence and refined privacy protection are realized, and the method has the advantages of high credibility, high intelligence and high traceability.

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.

The invention relates to the technical field of data processing, and discloses a block chain-based green product authentication traceability system. The system comprises a data acquisition module for acquiring product full-life-cycle green attribute data by using a multi-source sensing device; the block chain evidence storage module is used for hierarchically encrypting the data based on a hybrid hash algorithm to generate a non-tampering account book record; the intelligent contract auditing module automatically generates a green authentication result through a multi-rule verification model; the traceability query module is used for constructing a privacy protection query channel to output a verifiable traceability chain by applying a zero-knowledge proof technology; and the dynamic optimization module is used for adjusting the authentication standard according to the environmental policy change. According to the system, comprehensive acquisition, safe storage, accurate authentication, reliable tracing and standard dynamic optimization of green product data are realized, the authentication credibility and the supervision efficiency are improved, and the development of the green industry is promoted.

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 a data access permission control method and system based on a block chain, and relates to the technical field of block chains, the system is composed of a plurality of function modules, and the system comprises a hierarchical permission module which adopts a role hierarchical strategy and defines the access granularity of a role through an intelligent contract; the dynamic permission adjustment module is used for dynamically adjusting the permission range by analyzing user behaviors in real time through machine learning according to the principle of following the minimum permission in the permission distribution process; attribute encryption and zero-knowledge proof are introduced, an access key is dynamically generated according to user attributes, and sensitive information is hidden in the verification process; the multi-chain collaboration module is used for coding an intelligent contract through an authority rule, automatically executing access request verification, storing encrypted data through a private chain, managing an index and an access strategy through an alliance chain, isolating a storage domain from an access domain, and carrying out process traceability on a data request through a cross-chain verification mechanism; and the key management module is used for generating a true random number private key by adopting a hardware security unit.

The invention discloses a digital financial data sharing system and method, and belongs to the technical field of digital financial data analysis, and the system comprises a data standardization management module, a data access conversion interface module, a cross-mechanism authentication authority management module, a safety audit risk control module and an intelligent analysis cooperation platform module. The data standardization management module is used for unifying a data format to be XBRL, metadata definition and cleaning rules and eliminating data semantic differences between mechanisms, and the data access conversion interface module is used for supporting multi-source heterogeneous data access and providing a standardized output interface. The cross-institution authentication authority management module is used for realizing decentralized identity authentication based on a block chain technology, zero-knowledge proof and a federated learning technology, and controlling a data access range in a hierarchical manner in combination with role authority, and the security audit risk control module is used for monitoring data flow in real time. According to the invention, on the basis of realizing digital financial data sharing, the problem of data islands can be solved, and cross-mechanism data authentication can be facilitated.

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 provides a progressive privacy calculation method and system for a virtual-real fusion scene of an intelligent sweeper, and relates to the technical field of sweepers, and the method comprises the steps: collecting indoor space data through a multi-modal sensor, and constructing a scene knowledge graph through an entangled state registration network and a graph neural network; then, based on deep reinforcement learning and zero-knowledge proof, hierarchical encryption is carried out on the atlas, and scene data versions with different privacy protection intensities are generated through federated learning; and finally, performing path planning in a secure multi-party computing environment, and optimizing a cleaning strategy by using neural symbol reasoning and a graph attention network. According to the invention, scene understanding and path planning of the intelligent sweeper can be realized on the premise of guaranteeing the privacy of the user, the sweeping efficiency is improved, and the user experience is improved.

The invention relates to the field of medical examination data, and discloses a medical examination data sharing method based on cloud authentication, and the method comprises the following steps: carrying out the dynamic desensitization of original medical examination data at an edge node, and generating desensitization data meeting the privacy-utility balance; verifying the identity and authority of a request end user through a zero-knowledge proof protocol, and generating an authentication result bound with the privacy policy; performing hierarchical encryption on the desensitized data based on an anti-quantum attribute-based encryption algorithm to generate a ciphertext dynamically associated with the access attribute; and dynamically decrypting the data according to the real-time context parameters, and performing secondary desensitization processing in combination with an access scene. The technical scheme is optimized by adopting the dynamic desensitization and rate distortion theory, the technical effect of privacy-utility dynamic balance is achieved, and compared with the problems of fixed static desensitization rule and over-protection or under-protection in the prior art, the core defect that the method cannot adapt to the multi-scene data sharing requirement is overcome.

The invention relates to the technical field of medical information processing, in particular to a health data processing method and system based on a distributed ledger library, and the method comprises the steps: a node firstly links a health data abstract to obtain a differential privacy budget token and a reversible tensor hash key; then, carrying out encryption training on local model parameters by using the key, injecting Gaussian noise according to budget to generate a differential protection gradient, and carrying out uplink together with zero-knowledge proof; the account book end decrypts the threshold value, uses a structural equation model to deduce a causal correction matrix according to the reputation weight aggregation gradient, and automatically adds a budget and turns the key when the concept drifts and the budget is insufficient; the operation mechanism splices the aggregation parameters and local parameters, generates a gating vector in combination with a causal correction matrix and a reputation weight, outputs disease risk prediction, and only uploads prediction hash and error information; chain-level audible privacy protection, dynamic budget management and hybrid deviation suppression are realized, and the safety and accuracy of a cross-institution medical model are improved.

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 relates to a network security protection method and system based on a block chain, and aims to solve a series of challenges of identity authentication single-point failure, insufficient static block chain fragmentation, threat detection limitation, encryption algorithm security problem and the like in the existing network security protection technology. According to the method, an on-chain digital identity is generated by fusing an equipment unique identifier and user biological characteristics, dynamic authority management is performed based on the identity, network traffic is detected in real time by using a deep learning model of adversarial training, a threat detection result is generated, an authority level is updated according to the detection result through an intelligent contract, and meanwhile, the user experience is improved. A fragmented block chain network technology is adopted, the number of sub-chains is dynamically adjusted according to a network load, cross-chain threat intelligence synchronization is realized through a relay chain, in addition, a threshold signature and zero-knowledge proof technology is also adopted, permission change records and cross-chain data are encrypted and verified, the security and privacy of the data are ensured, and the security and privacy of the data are improved. According to the invention, the efficiency and reliability of network security protection can be effectively improved, and a safer and more reliable network environment is provided for users.

The invention discloses an energy storage transaction and carbon credit management system and method based on a block chain, and relates to the technical field of block chains, and the system comprises four modules: a dynamic carbon factor accounting module obtains data in real time, calculates the carbon emission reduction amount, and generates a carbon credit value; the heterogeneous cross-chain interoperation transaction module is connected with an energy chain and a carbon chain, and binds carbon credit and transaction records; the multi-target reinforcement learning energy storage scheduling optimization module is combined with a multi-target deep network algorithm to generate a strategy and a proportion; the enhanced carbon account module stores data and generates a voucher. The system has the advantages that data are acquired in real time through the dynamic carbon factor accounting module, the equivalent carbon emission reduction amount is calculated, the dynamic carbon credit value is generated, the problem of carbon credit calculation lag is solved, and accurate calculation and timely issuing of the carbon credit are realized; and meanwhile, by utilizing a hash time lock and a zero-knowledge proof verification mechanism of the heterogeneous cross-chain interoperation transaction module, the carbon credit is bound with the transaction record, and the energy chain and the carbon chain are connected, so that the mobility of the transaction and the integration of carbon emission reduction are improved.

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.

The invention discloses a data security method and system based on privacy computing and multifunctional encryption, and relates to the technical field of privacy security computing. Verifying the operation authority of the computing node on the encrypted data block through a zero-knowledge proof protocol, and generating a strategy compliance proof; a differential privacy budget real-time verification mechanism is adopted to verify the privacy protection intensity of strategy compliance proof, and a temporary permission token which passes authorization is obtained; based on the temporary permission token, performing encryption calculation allowed by strategy compliance proof on the encrypted data block through homomorphic operation, and generating an encryption calculation result and a calculation correctness proof; carrying out joint cryptographic packaging on an encryption calculation result, a strategy compliance proof and a calculation correctness proof, and outputting security data through a verifiable calculation protocol; according to the invention, through a differential privacy budget real-time verification mechanism and homomorphic and cryptomorphic calculation based on the temporary permission token, dual guarantee of privacy protection and data security is realized.

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 privacy protection and verifiable product carbon footprint evaluation method based on a block chain. The method mainly comprises the steps that a chain owner enterprise defines a purpose and a range; a chain owner enterprise requests carbon emission list data from an upstream raw material supplier according to a product material list (BOM), the raw material supplier performs homomorphic encryption on the carbon emission list data and then sends the data to a cloud computing platform of the chain owner enterprise, and identity verification is performed on a data source in combination with an RSA digital signature algorithm; the cloud platform completes carbon footprint calculation in a ciphertext state, and finally, a ciphertext result is returned to an upstream supplier; and the chain owner enterprise integrates the raw material supplier data through the cloud platform, completes final product carbon footprint calculation, verifies the validity of the calculation process based on a zero-knowledge proof technology, realizes automatic verification in combination with an intelligent contract, and finally explains and explains the whole process. According to the method, privacy protection of the carbon emission list data is realized, the evaluation process is verifiable, and the evaluation result is more accurate.

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 discloses a commodity transaction method and system for a block chain smart contract, and relates to the technical field of smart contracts, and the method comprises the steps: generating an entanglement particle pair through a quantum key distribution protocol, and generating an initial contract parameter package; when the commodity arrives at the logistics key node, generating a space-time stamp hash value, and writing the space-time stamp hash value into the block chain to generate a logistics event voucher; the intelligent contract monitors the logistics event voucher and outputs a verification signal to trigger payment; when the buyer and the seller are objection to the verification result, the smart contract randomly selects an arbitration node through a dark matter detector network; after zero-knowledge proof verification, weighted voting is carried out according to rules, funds are released through a cross-chain protocol, and the commodity ownership is unlocked; after arbitration and verification are completed, the smart contract calls a cross-chain protocol to release funds to the seller, and a closed-loop transaction voucher is formed; through the quantum entanglement particle pair and the gravitational wave sensor, high-precision time-space stamp verification is realized, and authenticity and non-tampering of logistics events are ensured.

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.

A computer implemented method for verifying a policy proof includes receiving request from a user for a policy, issuing a random challenge nonce, receiving a triple comprising a first genesis state of the user, a zero-knowledge proof of the policy based at least in part on the first random challenge nonce, an account address corresponding to the user, and user data, and a signature of the zero-knowledge proof of the policy, verifying the zero-knowledge proof of the policy based at least in part on the account address of the user, the first random challenge nonce, and one or more states of the user, storing the zero-knowledge proof and the policy identifier in a decentralized storage, publishing the account address corresponding to the user, the policy identifier, and a content identifier to one or more blockchain ledgers.