5538 results about "Ciphertext" 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.

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 provides a service data security protection method and system for digital enterprise management, and the method comprises the steps: obtaining an access request sequence initiated by a target user at a service operation terminal, generating a dynamic access control strategy vector according to a historical behavior track associated with an access operation identifier, and carrying out the dynamic access control strategy vector; analyzing the dynamic access control strategy vector through a strategy decoder, and generating a real-time access permission instruction; based on the real-time access permission instruction, performing homomorphic encryption mapping on a sensitive data segment in the request context information to generate a ciphertext transmission channel, and performing security parameter synchronization on the ciphertext transmission channel and the cross-department conjoint analysis model; and calling a federated learning framework to carry out multi-modal feature fusion on the real-time operation flow of the service operation terminal, generating an abnormal operation confidence score, triggering a cross-level interception protocol when the abnormal operation confidence score exceeds a dynamic threshold, and rolling back the current session state to a security baseline version. According to the invention, the accuracy and response timeliness of anomaly detection can be improved.

The invention discloses a data encryption and dynamic key management method based on a quantum security protocol, and the method comprises the steps: 1, selecting an initial quantum random seed and a classical entropy source seed, and generating a key at an initial moment; at each moment, forming an update increment through a nonlinear chaos increment and a fractal function, constructing a key update function, and updating the key; 2, preprocessing the original message into an integer vector; constructing a dynamic transformation matrix by using a secret key at the current moment, sampling from multi-dimensional Gaussian distribution to obtain a short vector, and constructing a public random matrix; encrypting the integer vector by combining the dynamic transformation matrix, the short vector and the public random matrix to obtain a ciphertext; and step 3, decrypting by using the secret key at the current moment and the dynamic transformation matrix which are synchronously updated, and recovering the original message. The invention provides a data encryption scheme with high security and quantum attack resistance.

The invention discloses a trusted data space cross-domain collaborative analysis method based on privacy computing, which comprises the following steps: step 1, trusted data space construction: edge computing nodes are deployed in a plurality of data owners participating in cross-domain collaborative analysis, and each edge computing node is interconnected through a block chain network to form a distributed trusted data space; a strategy engine is configured in the trusted data space, and the strategy engine is used for defining a data use permission, a privacy protection level and a calculation task life cycle management rule; and step 2, dynamically selecting privacy computing protocols, and selecting at least one privacy computing protocol from a pre-configured protocol library according to the data type, privacy protection requirement and computing complexity of the collaborative analysis task. When the scheme is implemented, the data participates in calculation in a ciphertext or desensitization form in the whole process, and the original data is not out of the domain, so that the privacy compliance requirement is met; and data use rules are automatically executed through block chain evidence storage and the intelligent contract, so that malicious node tampering is prevented.

The invention relates to the technical field of encryption communication, in particular to a data encryption communication method and system applied to an intelligent cash register. The method comprises the following steps: collecting user touch data and equipment hardware fingerprints, and carrying out high-dimensional feature fusion coding to obtain a joint identity certificate; obtaining an original key negotiation protocol and transmission metadata of an opposite-end server, and executing multi-logic path mapping and channel encryption configuration to obtain distributed ciphertext channel parameters; encrypting the distributed ciphertext channel parameters and the corresponding transmission metadata, and then performing block content packaging and node hash calculation to obtain an audit chain hash block; performing homomorphic encryption processing on the obtained real-time transaction data to obtain a to-be-transmitted homomorphic ciphertext; and performing communication transmission anomaly detection on information transmission data acquired in real time, and triggering dynamic key re-negotiation so as to improve the communication feedback capability. According to the invention, the overall security and stability of data encryption communication between the cash register and the back-end server can be improved.

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 discloses a driving vehicle road cloud collaborative safety management and control method and system based on trusted computing, and the method comprises the steps: generating an HMAC-SM3 data fingerprint through employing an SM3 Hash algorithm engine, and proposing an LSTM lightweight dynamic trust evaluation model based on a TinyML framework; through a step-by-step Hash verification and rollback mechanism, through Geohash coding and SM3 Hash joint calculation, based on an aggregation signature of a BLS12-381 curve and public key aggregation, the communication overhead during multi-RSU collaborative signature is reduced; distributed private key fragmentation decryption is realized by adding a homomorphic aggregation ciphertext; aggregating and delaying the compressed ciphertext; dynamically evaluating the credibility of the nodes by a Krum dynamic defense mechanism; the system comprises a vehicle side credible sensing layer, a roadside credible broadcast layer and a cloud credible decision-making layer. According to the invention, through layered credibility verification, dynamic trust chain extension and a data privacy protection mechanism, the security and credibility problems of multi-node cooperation in an automatic driving scene are solved.

The invention belongs to the technical field of digital information transmission, and relates to a vehicle-mounted ad hoc network security communication system and method based on an NTRU lattice cryptosystem, and the system comprises a message signature module, a message encryption module, a message decryption module, an identity authentication module, and a key exchange module. The message signature module carries out signature by utilizing a private key and a random polynomial dynamically generated by a pseudo-random number generator based on an NTRU lattice cryptosystem; the message encryption module encrypts a to-be-sent message by randomly selecting a temporary polynomial and combining a public key of a receiver; the message decryption module is used for decrypting the received ciphertext # imgabs1 # by using a private key and an inverse element # imgabs0 # of a module p of the private key; the identity authentication module is used for performing identity authentication; the key exchange module realizes secure key exchange between communication nodes in the vehicle-mounted ad hoc network through an improved Blom key distribution protocol. The system improves the security and communication efficiency of the vehicle-mounted network.

Some embodiments are directed to a computer-implemented method of determining encrypted computation parameters for carrying out an encrypted computation on noisy ciphertexts. A computation graph is divided into multiple subgraphs, defined by a type and by instantiation parameters for the type. Respective sets of encrypted computation parameters are defined for the respective types. An optimization of the encrypted computation parameters is performed to minimize a computational cost of carrying out the encrypted computation according to the encrypted computation parameters. The encrypted computation parameters are constrained to satisfy a noise constraint on ciphertext noise while carrying out the encrypted computation. The noise constraint is based on respective noise constraints for respective subgraphs, defined by a noise constraint function for the type that takes at least the encrypted computation parameters for the type and the instantiation parameters of the subgraph as input.

A method for performing a bootstrapping operation in cryptographic application, includes receiving in an accelerator one or more input ciphertexts used in the cryptographic application to be bootstrapped and iteratively processing one or more accumulator variables in function of portions of the input ciphertexts; multiplying, within each iteration, the processed accumulator variables with a bootstrapping key element belonging to a bootstrapping key comprising a plurality of bootstrapping key elements, said bootstrapping key element taken from a bootstrapping cache memory in the accelerator; while performing the multiplying for each of the one or more accumulator variables in turn, loading into the bootstrapping cache memory from an external memory a next bootstrapping key element of the plurality of bootstrapping key elements to be used in a next iteration of the bootstrapping operation.

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 provides a safety monitoring method and system for a financial information service platform. Wherein a collaborative encryption transmission channel between a budgeting unit and an auditing department is constructed, a joint key is generated based on a multi-party computing protocol, and the ciphertext operation authority of a sensitive field is dynamically configured; performing ciphertext variance calculation and regression analysis on the encrypted budget execution record through the security operation node, generating a verifiable statistical result, binding the authority, and synchronously updating the sensitive field access frequency; a hierarchical security threat baseline is generated in combination with permission, frequency and historical query records, and cross-project high-frequency query and data operation deviation are associated; and when the query deviates from the baseline, calculating the risk confidence coefficient according to the deviation, triggering multi-party verification path adjustment and collaborative alarm, and dynamically limiting the ciphertext permission of the abnormal query. According to the technical scheme provided by the invention, cross-department data security sharing and dynamic risk collaborative prevention and control are realized.

The invention discloses an industrial internet data security communication method based on hybrid anti-quantum cryptography, which relates to the technical field of data communication, and comprises the following steps: acquiring a key pair and an anti-quantum security certificate; sending a connection request to data receiver equipment to complete certificate credibility authentication, and sending an anti-quantum security certificate of the equipment; receiving a shared key seed sent by the data receiver equipment; decrypting the encapsulated ciphertext to obtain a shared key seed, and generating a corresponding shared key according to the same shared key generation algorithm as the data receiver equipment; the method comprises the following steps of: signing original data by using a signature private key, splicing a signature and the original data to obtain spliced data, encrypting the spliced data by using a shared key based on an AES-256-GCM algorithm to obtain an encrypted ciphertext and an ML-DSA signature, and sending the encrypted ciphertext to data receiver equipment. According to the method, the key distribution step is simplified, the signature verification calculation overhead is optimized, and the data communication efficiency is improved.

The invention discloses a data processing method based on computer software development, which belongs to the technical field of data processing, and comprises the following steps: S1, constructing an adaptive analysis engine driven by a knowledge graph, and carrying out multi-modal data semantic modeling and context labeling by adopting a multi-modal data feature fusion technology; and S2, designing a cross-node distributed data cleaning and dynamic fragmentation optimization strategy based on a differential privacy and feature space alignment technology, and through hierarchical deployment of a national cryptographic algorithm and homomorphic encryption, realizing data full life cycle security protection, ensuring data asset security by static storage encryption, and supporting security calculation requirements by ciphertext operation; attribute-based encryption fine-grained access control accurately matches a data use permission, and a block chain technology ensures traceability and tamper-proofing of data operation; the problem that a traditional encryption scheme is insufficient in flexibility is solved while the compliance requirement is met, and a trusted infrastructure is established for cross-domain data sharing.

The invention relates to a multi-medical image encryption method based on a three-dimensional hyperchaotic system, and belongs to the technical field of medical image encryption. According to the method, in an image preprocessing stage, dual medical images are fused through an Alpha channel to generate a to-be-encrypted matrix, an SHA-512 function is combined with RGB and an Alpha channel matrix to generate a key sequence, and a dual-key matrix and a chaotic sequence are generated through a three-dimensional hyperchaotic Logistic-Sink (3D-HCLSM) system; in the encryption stage, triple encryption operations are implemented: a parameter randomization dynamic Josephh scrambling strategy is adopted to generate a primary ciphertext, an improved zigzag bidirectional cross permutation strategy is adopted, pixel diffusion with a key matrix is carried out to obtain a secondary ciphertext, a novel bit-level scrambling strategy is carried out, and bit XOR operation with the key matrix is carried out to complete final encryption. According to the method, a dynamic Joseph traversal mechanism with random parameters is provided, an optimized zigzag replacement strategy and a novel bit-level processing technology are combined, and the attack resistance and safety of medical image encryption are remarkably improved through the synergistic effect of multi-level chaos secret keys.

The invention belongs to the technical field of computer data security, and discloses an enterprise data encryption storage system based on strategy optimization. The system is composed of a strategy map construction and optimization module, a sensitivity identification and encryption strategy generation module, an encryption execution and ciphertext structure processing module, a strategy-driven storage scheduling module and an audit recording and feedback optimization module. According to the method, a strategy graph containing multiple types of nodes such as users, data, behaviors, risks and resources is constructed, the edge weight and the node confidence coefficient are dynamically adjusted through the behavior frequency, the access relation and historical audit information, a graph structure oriented to behavior contexts is formed, and on the basis, an encryption strategy label is generated in combination with a fuzzy semantic reasoning mechanism; a traditional static recognition mode based on field rules can be broken through, potential high-sensitivity data and abnormal behavior paths are recognized, and the generation accuracy and the self-adaptive capacity of a data encryption strategy are improved.

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 discloses an anti-quantum security identity authentication method and system, a medium and equipment. The method comprises the following steps: S1, a client, a service server and a key distribution center perform key configuration by adopting a digital signature algorithm; s2, the client sends an authentication request to the authentication server, and receives an authentication response with a bill granted bill returned by the authentication server; s3, the client sends a bill request to the bill issuing server, and receives a bill response with the service bill returned by the bill issuing server; s4, the client generates a client key exchange public key by adopting a first key exchange algorithm and sends an access request, the service server calculates a shared key and a ciphertext after receiving the public key, generates an access response comprising the ciphertext and identity information encrypted by using the shared key, and returns the access response to the client; and S5, the client receives the access response and obtains the shared key, and performs encrypted communication with the service server by using the shared key. The method has forward safe quantum attack resistance and strong identity authentication.

The invention relates to the technical field of noise maps, in particular to a noise map dynamic deduction method and system based on multi-source heterogeneous data fusion, and the method comprises the steps: carrying out the space-time alignment of a multi-cluster low-dimension feature vector in an edge calculation node, and obtaining a multi-cluster low-dimension feature vector; generating a three-dimensional sound field reconstruction parameter of the first target data sequence and a spectrum energy distribution parameter of the second target data sequence; based on the three-dimensional sound field reconstruction parameter and the spectrum energy distribution parameter, dynamically controlling the sensor cluster to sleep and generating a space-time difference parameter; hierarchical encryption is carried out on the time-space difference parameters and the two types of data sequences in the dormancy period, and a basic ciphertext sequence and a feature ciphertext sequence for verification are generated; according to the method, the noise deduction map with space-time continuity is generated, high-precision dynamic deduction and energy efficiency optimization of the noise map are achieved, the evolution rule of noise along with time and space is effectively reflected, the real-time performance and accuracy of noise data are improved, and the actual situation of the noise can be reflected more truly, efficiently and in real time.

The invention relates to the technical field of cloud computing financial security, and provides a financial data encryption transmission and storage method. The method is characterized by comprising the following steps of: executing sensitivity-driven data grading fragmentation on a user terminal; dynamic elliptic curve encryption is carried out on transmission data through a two-channel encryption engine, and fully homomorphic encryption is carried out on storage data; dynamically distributing the fragments to heterogeneous cloud nodes by the multi-cloud routing based on reinforcement learning; a distributed key management matrix is constructed, key fragments are dispersed and stored in a block chain and a hardware security module, and reconstruction is activated through biological characteristics. The method has the advantages that full-link ciphertext operation is realized, and the plaintext exposure risk is eliminated; ciphertext state financial calculation is supported; single point failure is resisted; the APT attack is defended dynamically; and the quantum security evolution capability is realized. The method is suitable for mobile banks, cross-border payment and other scenes.

The invention discloses a finance and taxation data intelligent management method and system based on encrypted storage, and relates to the technical field of enterprise finance and taxation management, and the method comprises the steps: collecting finance and taxation related data from a plurality of channels through a data obtaining module, carrying out the sensitivity evaluation of the data, and dividing the sensitivity grade; key generation and encryption strategy setting: making a corresponding encryption scheme according to the sensitivity level of the data, including generation of an encryption key and setting of a dynamic encryption strategy; data encryption and storage: carrying out encryption processing on finance and tax data by utilizing the obtained secret key and the encryption strategy, and safely storing a ciphertext; and data access and dynamic encryption maintenance: providing a controlled encrypted data access service, and executing dynamic security maintenance on the stored data according to a predetermined strategy. According to the invention, the finance level, the intelligent degree and the long-term compliance of finance and tax data protection are effectively improved.

The invention provides a multi-authentication electronic official certificate verification method and system based on a block chain, and relates to the technical field of block chains, and the method comprises the steps: receiving an electronic official certificate uploading request, carrying out encryption processing to generate a secret key, carrying out the block encryption of an official certificate file to obtain an electronic ciphertext, carrying out the authentication of a creator identity to obtain an elliptic curve digital signature, and carrying out the verification of the elliptic curve digital signature. Writing in a new block, and calculating a block hash value; the target block is inquired, and if matching succeeds, the first verification information is extracted and verified, and a comprehensive verification result is generated; and carrying out consensus verification, modifying the block outlet time by dynamically adjusting the block difficulty value and verifying, if the block outlet time is true and effective, generating a verification result ciphertext and feeding back the verification result ciphertext to the request main body, and if objection exists, sending an objection application and carrying out objection rechecking, generating an arbitration result and writing the arbitration result into the new block.

The invention relates to the technical field of block chains, and discloses a block chain and privacy computing collaborative verification system, which comprises a data fragmentation module, a privacy fusion module, a collaborative verification module, a consensus correction module and a fragmentation graph optimization module. The data fragmentation module constructs a multi-stage data collaborative topology through a preprocessing node and a dynamic fragmentation protocol; the privacy fusion module realizes privacy protection by using a ciphertext analysis unit to switch links in a multi-state manner and a zero-knowledge verification unit; a collaborative verification module generates a reference verification strategy through a consensus modeling node multi-dimensional fusion model, and a state optimization unit dynamically aggregates and sorts fragmentation states; the consensus correction module corrects the fragmentation state through an isolation verification unit and a delay compensation unit and calibrates ciphertext parameters; and the fragment atlas optimization module constructs a stability evaluation network monitoring synchronization rate and performs closed-loop adjustment on a verification strategy. The system realizes dynamic fragmentation, privacy fusion and intelligent verification, and improves the efficiency, security and stability of block chain data processing.

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

The invention discloses a cross-regional cross-mechanism health medical data security sharing method based on a block chain, and relates to the technical field of data security, and the method comprises the steps: 1, carrying out the content balance fragmentation of an electronic health record, and obtaining a plurality of content fragments, encrypting each content fragment by using a random salt value generated by the head hash value of the previous height block to obtain a salt-added ciphertext fragment; 2, calculating a hash sequence for all salted ciphertext fragments of the same patient and generating a Merkel root; 3, when the external medical institution makes an access application, the chain smart contract compares the identity code set of the applied external medical institution with the patient agreement white list; and when an agreement threshold value set by the patient is met, generating and verifying an access authorization token by adopting a signature mechanism, and writing an authorization result into a block chain auditing side chain. According to the method, the problems of low data sharing efficiency, high trust dependence, difficulty in auditing and the like in a traditional mode are solved.

According to the face data privacy protection method and device provided by the embodiment of the invention, a credible authority management mechanism is constructed through a distributed network and a smart contract, and a multi-dimensional feature extraction scheme fusing geometric features and texture features is innovatively designed. The system adopts data fragmentation and homomorphic encryption technologies to carry out security processing on feature vectors, and dispersedly stores encrypted data in a block chain network, so that decentralized management of the feature data is realized. According to the method, feature comparison and identity verification are carried out in a ciphertext domain, the whole process is traceable in combination with a timestamp and an operation record, the problems of data security and privacy protection in a traditional face recognition system are effectively solved, and a safe and credible technical solution is provided for the field of biological feature recognition.

The invention provides an image data secure transmission method, computing equipment and a computer storage medium. The method is applied to a data sender, and comprises the following steps: executing a first image encryption algorithm, and performing encryption processing on a transmission image through an image key to obtain a ciphertext of the transmission image; executing a first key encryption algorithm, and performing encryption processing on the image key through an encryption key to obtain an encrypted image key; the first image encryption algorithm is different from the first key encryption algorithm; and forming a transmission data packet from the ciphertext, the encryption key and the encrypted image key, and transmitting the transmission data packet to a data receiver. Therefore, a proper image encryption algorithm is adopted for the image data, and a proper key encryption algorithm is adopted for the image key, so that real-time performance and security are both considered in the image data encryption process through a mixed encryption mode.

The invention provides a privacy protection-based graph data constraint shortest path verification query method and system, and the method comprises the steps: obtaining a path query request sent by a user side, carrying out the encryption processing of target graph data, generating an encrypted graph structure feature, and segmenting the encrypted graph structure feature into a first encrypted sub-feature and a second encrypted sub-feature; calling a pre-trained key segmentation model to match the path constraint condition with a preset privacy policy, generating a verification token, sending the first encryption sub-feature and the verification token to a first computing node through a distributed protocol, and sending the second encryption sub-feature and the verification token to a second computing node, and triggering the first computing node and the second computing node to execute secure multi-party computing, outputting the candidate path ciphertext and the verification parameter set, performing consistency verification, and if the verification is passed, performing decryption processing to generate a target shortest path meeting a path constraint condition. According to the method, a solution which takes privacy protection, result accuracy and calculation efficiency into consideration is provided for a high-security scene.

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.