7563 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 provides a security management and retrieval method based on Internet of Vehicles data, and the method comprises the steps: carrying out the cooperative training of a global key management model through a federated learning technology on the premise of not leaking the original data of all parties, and achieving a security key management scheme under the participation of multiple parties through a model parameter aggregation and updating mechanism; when data retrieval is needed, a user submits a retrieval request and identity authentication information, and after a system verifies the identity of the user, a ciphertext data identifier meeting conditions is matched in an attribute index according to a keyword and an authorization attribute of the request; the system acquires corresponding ciphertext data from a distributed database according to the ciphertext data identifier, and directly performs keyword matching calculation on the ciphertext data through a secure multi-party computing protocol under the condition of not decrypting the data; and according to the mined security threats and abnormal modes, a data encryption strategy and an access control strategy are dynamically adjusted, authority limitation or access blocking is performed on suspicious users, and the security protection capability of the system is improved.

The invention provides an energy storage power station battery health state diagnosis method and system based on big data, and relates to the technical field of energy storage batteries, and the method comprises the steps: collecting multi-mode operation data of an energy storage power station battery, carrying out homomorphic encryption to obtain ciphertext data, carrying out analysis and calculation, extracting explicit and implicit correlation features, and obtaining fusion time sequence data; based on fusion time sequence data, extracting multi-path quantum entanglement features, combining with a self-evolution quantum attention mechanism, dynamically adjusting the phase and amplitude of quantum bits, generating diagnosis feature enhancement representation, realizing entanglement storage through a quantum circuit, and combining with a gating unit to predict a health state sequence; and determining a battery health prediction result, and obtaining a battery health state diagnosis result by combining quantum state superposition and quantum parallelism, searching a diagnosis strategy combination space on line, embedding a multi-order causal relationship tensor model, modeling causal relationship strength between battery performance indexes, determining a battery health degradation index, generating a causal diagnosis map and obtaining the battery health state diagnosis result.

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 relates to the technical field of information, and discloses a ciphertext execution exception handling method and system for a privacy computing algorithm, which quantifies the data query sensitivity of each tenant by collecting differential privacy query parameters of a plurality of tenants, and performs time sequence analysis on the sensitivity quantification result by using an ARIMA model to predict the future trend of the tenant, so as to improve the accuracy of the ciphertext execution exception handling of the privacy computing algorithm. The residual error between the actual sensitivity and the predicted sensitivity is calculated to identify abnormal tenants; a sliding window method is adopted to extract statistical features of the abnormal tenants to construct a feature set, and clustering analysis is carried out on the feature set to identify abnormal modes and abnormal fingerprint feature clusters corresponding to the abnormal tenants; and training a model based on the positive and abnormal fingerprint feature clusters of the abnormal tenants, and quantifying the influence degree of each abnormal mode on the privacy protection level of the abnormal tenants by using the model, so as to adjust and execute the privacy budget allocation proportion of each abnormal tenant according to the obtained quantitative analysis result. And therefore, the exception in the ciphertext execution of the privacy calculation algorithm can be effectively processed.

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 provides an identity information dynamic desensitization method and system based on SM4 and SM9 algorithms, and the method comprises the steps: carrying out the data segmentation of original identity information, and obtaining sensitive segment information and common segment information; performing key dynamic generation based on an SM4 algorithm, and encrypting the sensitive segment information to obtain encrypted sensitive segment information; extracting a feature value of the common segment information through a preset hash function, and converting the feature value into coded data in a preset format to obtain converted common segment information; splicing the converted common segment information and the encrypted sensitive segment information to obtain preliminary desensitized data; and encrypting the preliminary desensitized data based on an SM9 algorithm to generate an encrypted ciphertext, and embedding a unique identity identifier associated with the original identity information into the encrypted ciphertext in an encryption mode to obtain desensitized identity information. According to the invention, the dynamic desensitization of the identity information can be realized, and the data format can be kept unchanged.

A computer-implemented method for performing at least one computational operation on an encrypted input by at least one processor of a server in a client-server setting, where parameters of the computational operation are private to the server and the input is private to the client is provided. The method includes receiving, by the server, a ciphertext c of a leveled homomorphic encryption (LHE) scheme as encrypted input. Randomness is homomorphically added by the server to the ciphertext c and the resulting ciphertext b is transmitted to the client. The server receives a refreshed ciphertext b′ obtained by the client in a ciphertext refresh procedure including decrypting and re-encrypting the ciphertext b. The server homomorphically removes the previously added randomness from the received refreshed ciphertext b′ to obtain a refreshed ciphertext c′. The server performs the at least one computational operation on the refreshed ciphertext c′.

The invention provides a privacy protection method and system based on big data security and privacy calculation, and relates to the technical field of data processing, and the method comprises the steps: obtaining original data feature extraction, obtaining data features, selecting a data desensitization algorithm to carry out data desensitization, carrying out encryption processing through a hybrid fully homomorphic encryption algorithm, and carrying out encryption processing through a hybrid fully homomorphic encryption algorithm. Homomorphic encrypted ciphertext data is generated and sent to the privacy protection computing platform; a data preprocessing protocol for privacy protection is constructed, data filtering and data dimension compression are carried out, multi-party security calculation is executed, a ciphertext calculation result is generated and returned to a data provider, verification is carried out, and if verification passes, decryption and filtering are carried out through a decryption algorithm to obtain a pure plaintext calculation analysis result; and constructing a reverse data desensitization model for reduction to obtain an analysis calculation result, constructing a dual-target optimization model for solving, obtaining an optimal balance point and generating an optimal decision result, desensitizing, uploading to a privacy protection block chain network, and performing distributed credible storage and sharing.

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.

The present application provides a universal quantum secure device and methods of sending and receiving data. A quantum encryption and decryption module can realize quantum encryption and decryption of data requiring quantum encryption service, thereby ensuring that data sent and received by the universal quantum secure device from a conventional network are transmitted in ciphertext form. An isolation module can realize isolation between the communication module and each of the quantum encryption and decryption module and a privacy module, so that security of the privacy module and security of the quantum encryption and decryption module are protected from being affected by data received by the communication module from external network. Since the privacy module does not communicate with external network, and encryption and decryption of the data can only be carried out in the quantum encryption and decryption module of the universal quantum secure device, improving data security.

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.

A set of distance measurable encrypted feature vectors can be derived from any biometric data and / or physical or logical user behavioral data, and then using an associated deep neural network (“DNN”) on the output (i.e., biometric feature vector and / or behavioral feature vectors, etc.) an authentication system can determine matches or execute searches on encrypted data. Behavioral or biometric encrypted feature vectors can be stored and / or used in conjunction with respective classifications, or in subsequent comparisons without fear of compromising the original data. In various embodiments, the original behavioral and / or biometric data is discarded responsive to generating the encrypted vectors. In another embodiment, distance measurable or homomorphic encryption enables computations and comparisons on cypher-text without decryption of the encrypted feature vectors. Security of such privacy enabled embeddings can be increased by implementing an assurance factor (e.g., liveness) to establish a submitted credential has not been spoofed or faked.

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 provides an electronic book file secondary encryption method based on MD5 encryption and an asynchronous request, and relates to the field of data processing. Comprising the following steps: firstly, acquiring a current timestamp, a network state, a user request attribute and a system load state through a data acquisition module, and then performing MD5 preliminary encryption on an electronic book file to generate a first layer of ciphertext; segmenting the first-layer ciphertext and transmitting the segmented first-layer ciphertext to an encryption module through an asynchronous request; a self-adaptive distributed load balancing mechanism is adopted to monitor the system state through an encryption module, resources are dynamically allocated, and tasks are scheduled; in combination with intelligent priority scheduling, determining the priority according to the attributes of the data segments; generating a dynamic key based on a timestamp, a network state and the like to encrypt the data segment in real time; and finally, sorting, checking and combining the encrypted data segments into a complete ciphertext file.

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.