51 results about "Chinese remainder theorem" patented technology

The invention discloses an anti-quantum key management method for a vehicle-mounted domain centralized electronic and electrical architecture. Firstly, the invention provides a self-adaptive security policy generation method based on an analytic hierarchy process. Key factors influencing vehicle-mounted service safety are sorted through a system, a three-layer AHP hierarchical structure model with the purpose of selecting an optimal encryption mechanism is constructed, and therefore vehicle-mounted service safety modeling is achieved. According to the method, the most suitable security policy can be automatically matched according to the characteristics of different services, the self-adaptive security policy generation of the service granularity is realized, and the optimization of the system resource use efficiency is realized while the communication security is ensured. Secondly, the invention provides a fine-grained anti-quantum key management scheme based on the Chinese remainder theorem, and the fine-grained anti-quantum key management scheme is specially designed for adapting to a one-to-many communication scene widely existing in a vehicle-mounted network. The method supports efficient distribution and dynamic updating of group keys of service granularity, and has good quantum attack resistance.

The invention provides a network intrusion detection method based on a federated graph neural network, which comprises the following steps: carrying out graph structure modeling on network flow data, constructing a local sub-graph of each client, adopting a federated learning framework, carrying out graph neural network model training by the client locally through the local sub-graph, and obtaining a network intrusion detection result; and the encrypted data and model parameters are uploaded to the server, so that the potential safety hazard of data sharing is avoided. And the server aggregates the encrypted remainder set and the model parameter from each client, generates a global model parameter and an aggregated encrypted remainder set, and feeds back the global model parameter and the aggregated encrypted remainder set to the client to realize cross-client collaborative training. The encrypted data is decrypted by introducing the Chinese remainder theorem, so that the security and privacy of the data are ensured, and the feature reconstruction precision is improved at the same time. According to the method, the problem of data islands in cross-organization cooperation is effectively solved, and the real-time performance and accuracy of an intrusion detection system are improved on the premise of ensuring privacy protection.

The invention discloses an unmanned aerial vehicle cluster dynamic cross-domain key management method and system based on the Chinese remainder theorem (CRT), a key generation center generates system public and private keys and public parameters, and a ground station and an unmanned aerial vehicle perform hierarchical registration and verify respective keys; the unmanned aerial vehicles respectively generate signature messages and send the signature messages to a specified ground station for identity verification, and the ground station constructs a group key based on CRT and publishes the group key to the block chain; when a new unmanned aerial vehicle applies for joining, a signature message is sent to the ground station, and the ground station updates and publishes the group key; when the unmanned aerial vehicle applies for leaving, a leaving message is sent to the ground station, and the ground station updates and publishes the group key. According to the method, complex operations such as bilinear pairing operation and large integer modular exponentiation operation are avoided by optimizing the group key derivation process based on the CRT, and the calculation complexity is remarkably reduced. Meanwhile, efficient cross-domain authentication and batch verification are realized through Pedersen commitment and a zero-knowledge proof technology, and communication and calculation overhead is reduced.

The invention belongs to the technical field of cryptography and secure multi-party computing, and provides a homomorphic encryption multiplication triple generation method and system based on the Chinese remainder theorem.A data application party and a data provider generate private random vectors respectively, and the private random vectors are decomposed into a plurality of component matrixes by means of the Chinese remainder theorem; the data provider executes ciphertext multiplication and addition operation in the corresponding parallel channels according to the number of the component matrixes, the ciphertext of each channel is calculated based on a BFV homomorphic encryption algorithm, and the ciphertext result is sent to the data application party; and the two parties decrypt each ciphertext by using the private key to obtain a plaintext component matrix, reconstruct through the Chinese remainder theorem to obtain a plaintext vector, and calculate a local triad component based on the plaintext vector to generate a triad, and the triad meets the multi-party multiplication constraint. According to the method, the Chinese remainder theorem and the homomorphic encryption algorithm are ingeniously combined, efficient and extensible multiplication triple generation is achieved, and the efficiency and space limitation in the prior art is broken through.

The invention discloses a quantum security verifiable secret sharing method and device, equipment and a storage medium, is applied to a secret holder, and relates to the technical field of network security, and the method comprises the steps: determining a secret extraction polynomial of a target secret, and determining a target polynomial for determining a share; determining each secret share by using a hidden polynomial, a target secret, a secret extraction polynomial and a target polynomial; determining a fingerprint value based on a polynomial set and the target polynomial; determining a commitment value by using a share distribution polynomial, an auxiliary polynomial and the fingerprint value; sending the secret shares and the target polynomial to each participant; the participant verifies the secret share and the target polynomial; and if the verification is passed, the target secret share passing the verification and the corresponding target polynomial are disclosed, and the Chinese remainder theorem is utilized to carry out secret recovery to obtain the target secret so as to complete the corresponding secret sharing operation. And a verifiable function of secret sharing is realized at low cost.

A frequency estimation method based on time-delay sampling is suitable for signal processing in an engineering scene in which leaf end timing, nondestructive testing or passive radar is difficult to deploy a high-sampling-rate or multi-sampling-rate system, and comprises the following steps: uniformly sampling signals by using two channels with the same sampling period; the time delay and the sampling period of the two sampling channels are relatively prime; carrying out Hilbert transformation preprocessing on data points of the two sampling channels, and solving aliasing frequency in cooperation with an ESPRIT algorithm; changing the initial position of the analysis data to construct a plurality of delay schemes, and repeating the step S2 to obtain equivalent sampling frequencies and equivalent aliasing frequencies under different delay schemes; according to the equivalent aliasing frequency, calculating two remainder frequencies under each delay scheme; and performing traversal solution on the congruence equation set with the equivalent sampling frequency as the modulus and the remainder frequency as the remainder by using the Chinese remainder theorem, and obtaining the target frequency in combination with the consistency criterion and the minimum estimation criterion.

The invention discloses a blockchain and game theory enabling privacy enhancement federal learning method and system, and relates to the technical field of privacy protection. The invention aims to solve the problems of single-point fault risk, data privacy leakage hidden danger, Byzantine attack threat and the like when an industrial institution with harmonic reducer data uses federal learning to train a global fault diagnosis model. According to the technical key points, the method comprises the following steps: firstly, enabling federal learning of a block chain, and proposing a decentralized training framework; secondly, a privacy protection method fusing the Chinese remainder theorem and the shamir secret sharing technology is provided, and dual privacy protection is flexibly provided for participants; then, the homomorphic characteristic of the privacy enhancement method is utilized to defend Byzantine attacks, and the robustness of a federated learning system is improved; and finally, designing an incentive mechanism based on the game theory, inhibiting malicious behaviors in the training process, and realizing collaborative security of all parties. Experiments show that compared with a baseline scheme, the test accuracy of the BGFL is improved by 0.93%-22.75%; compared with a comparative federated learning scheme based on secret sharing, the BGFL can achieve the goals of safety, robustness and the like only with the calculation overhead and the communication overhead of 5.91% and 4.01%.

The application relates to the technical field of information security, and particularly discloses a homomorphic encryption method and system based on the Chinese remainder theorem, which comprises the following steps: a client initializes system parameters and generates an encoding modulus base; the client generates an encryption key through the system parameters and a random number generator; the client uses the Chinese remainder theorem to encrypt a message plaintext into ciphertext by using the encoding modulus base and the encryption key, and sends the ciphertext and the encoding modulus base to a server end; the server end performs homomorphic calculation on the ciphertext through the encoding modulus base to generate a homomorphic operation result; and the server end decrypts the homomorphic operation result by using the encryption key. The application can significantly compress the ciphertext size and greatly reduce the communication and storage overhead of the system.

The application discloses a privacy-enhanced data aggregation method supporting off-line fault tolerance and deviation correction. The method efficiently packs multi-dimensional data by using the Chinese remainder theorem, and realizes ciphertext aggregation without a fully trusted third party by introducing a collaborative mask based on neighbor relationship and a special mask shared by SM and CC, thereby guaranteeing data and identity privacy. Meanwhile, a deviation correction recovery mechanism executed unidirectionally by a control center is designed. The mechanism reconstructs a residual mask by using information such as a frozen candidate set and an effective participation set, thereby recovering a real aggregation result without requiring a node to respond secondly or an off-line node to supplement transmission. Performance evaluation shows that, compared with existing advanced schemes, DBPMDA reduces the additional communication and calculation overhead of the system in the case of device off-line, and is suitable for a resource-limited smart grid Internet of Things environment.

The invention discloses a group authentication and key agreement method suitable for a wireless sensor network, which realizes security authentication and key agreement between a sensor node and a sink node in the wireless sensor network by using a (t-1)-order binary variable symmetric polynomial, a secret sharing technology and a Chinese remainder theorem. Specifically, the method comprises the steps of registration center initialization, sensor node registration, aggregation node registration, secret reconstruction factor collection, secret value reconstruction and authentication, session key calculation and integrity verification. According to the method, complex cryptographic operation is not needed, authentication steps are simplified, data security is enhanced, dynamic addition of a new sensor node is supported, the finally negotiated session key does not depend on a secret value recovered by a sink node, and various security risks are effectively defended. The method is suitable for wireless sensor equipment with limited resources, various attack means can be resisted, and the information security of the wireless sensor network is ensured.

A method, apparatus and computer program product for privacy-preserving homomorphic inferencing using one-hot data representations. In this approach, a client interacting with a cloud-based server submits one-hot maps of a Chinese Remainder Theorem (CRT)-based representation of an data element, and the server expands these maps in an online phase to obtain a full one-hot map for the element. After the server obtains the full one-hot map, it performs an operation, e.g., a comparison operation associated with inferencing on a decision tree, on the one-hot map under homomorphic encryption, and in response generates a result. The result is provided back to the client.

The present application relates to the technical field of information security, and especially relates to an index-based single-server anonymous query method, which is applied to an index-based single-server anonymous query system, the system comprising a database server and at least one user terminal in communication connection with the database server, and the method comprising the following steps: S1, an inadvertent transmission protocol between a pre-constructed user terminal and a database server receives a first input query index of a user and returns a decryption parameter corresponding to the query index to the user terminal; S2, the user terminal acquires a query result corresponding to the query index according to the decryption parameter and a grouping data packet sent by the database server to the user terminal; the grouping data packet is obtained by the database server from n stored data by using the Chinese remainder theorem for preprocessing; each stored data comprises data information and a query index corresponding to the data information.

The present application relates to a kind of federal big model privacy protection methods based on CRT-BFV homomorphic encryption, belong to federal learning, big model privacy protection technical field.The method includes: according to model initialization parameter, training client, obtain client model weight, compress client model weight based on Chinese remainder theorem, obtain client one-dimensional weight;Using homomorphic encryption algorithm, client one-dimensional weight is encrypted, and ciphertext weight is obtained;Server is aggregated to the ciphertext weight uploaded, and aggregation result is obtained;Client decrypts the received aggregation result, obtains plaintext information and reconstructs, and obtains reconstructed plaintext information;After adjusting and updating reconstructed plaintext information, as the input of next round training, iteration training is carried out.The present application is aimed at solving the technical problem that "privacy-efficiency-accuracy" is difficult to balance in the related art in federal big model training.

A DOA estimation method of a delayed co-prime sparse linear array is suitable for signal processing of DOA estimation of radar, sonar and wireless communication, and comprises the following steps: measuring a signal source by using the delayed co-prime sparse array to obtain a signal sample; constructing two uniform subarray segmentation schemes with different delays, and segmenting the signal sample to obtain data; analyzing the segmented data by using a unitary ESPRIT algorithm to obtain a winding phase; and constructing a congruence equation set for each pair of wound phases, and solving the congruence equation set by using a robust Chinese remainder theorem algorithm to obtain a DOA estimated value.

The invention relates to the technical field of information security, in particular to an index-based single-server hidden query method, which is applied to an index-based single-server hidden query system, and the system comprises a database server and at least one user terminal in communication connection with the database server, the method comprises the following steps of: S1, receiving a query index input by a user for the first time by a pre-constructed casual transmission protocol between a user terminal and a database server, and returning a decryption parameter corresponding to the query index to the user terminal; s2, the user terminal obtains a query result corresponding to the query index according to the decryption parameter and a grouped data packet sent to the user terminal by the database server; the grouped data packet is obtained by preprocessing n pieces of storage data pre-stored by the database server by adopting the Chinese remainder theorem; each piece of storage data comprises data information and a query index corresponding to the data information.

The invention discloses a multi-feature hidden trace query method and system based on custom strength of a national cryptographic algorithm. A query party generates task configuration parameters of a query task; the queried party audits the task configuration parameters, after the task configuration parameters pass the auditing, a secret key pair of a domestic cryptographic algorithm SM9 is generated, and a public key in the secret key pair is sent to the query party; the query party generates a random number, encrypts the random number based on the public key, and sends the encrypted random number and query conditions in the task configuration parameters to the queried party; generating an original query result based on the query condition, and decrypting the encrypted random number through a private key to obtain a decrypted random number; the queried party encrypts the original query result based on the decrypted random number through the Chinese remainder theorem to generate an encrypted query result, and sends the encrypted query result to the query party; and decrypting the encrypted query result based on the random number by a Chinese remainder theorem query party to obtain a query result.

The invention provides an electronic signature dynamic permission allocation method and system. The method comprises the following steps: generating a dynamic permission baseline based on a system unpredictable entropy source and a real-time timestamp; mapping the permission base line into a permission network for sensing the signature operation risk; decomposing each edge used for representing the signature operation authority in the authority network into authority remainder components corresponding to the co-prime modulus; calculating a two-factor attenuation coefficient according to the signature operation time and the number of times, so that the signature authority effectiveness is naturally reduced along with the time lapse and the increase of the use frequency; and during signature operation, combining permission remainder components in real time, reconstructing a complete signature permission through the Chinese remainder theorem, and comparing the complete signature permission with a current permission baseline to realize non-exposure verification of the signature operation. According to the method, dynamic, safe and fine-grained distribution and verification of the signature authority are realized, the security and flexibility of signature authority management are remarkably improved, the whole signature process is efficient and accurate, sensitive information is not leaked, and a solid guarantee is provided for security application of a signature system.

The present invention discloses a multi-baseline phase unwrapping method of a robust Chinese Remainder Theorem considering branch cut lines. The method comprises the following steps: generating multi-baseline InSAR phase interferograms for the same region of interest; setting branch cut lines for the interferograms by using the branch cut method, and obtaining unwrapped phases in a large range by using the Chinese Remainder Theorem to avoid the branch cut lines through appropriate means; generating local branch cut lines for the branch cut line distribution region, and performing unwrapping again by using the Chinese Remainder Theorem; combining the phase unwrapping information of the large range region and the local region to obtain the final phase unwrapping information. This solution uses branch cut lines and an adaptive rectangular box to extract regions with strong noise, uses relevant filtering algorithms to weaken the interference of noise on interferometric phase information, uses the Chinese Remainder Theorem algorithm twice to unwrap the large area region with weak noise information and the local region with strong noise information respectively, and splices the unwrapped phase information to implement an anti-noise multi-baseline phase unwrapping algorithm.

The invention discloses a cross-domain data management method and device based on federal intelligence, and relates to the technical field of federal learning. The method comprises the following steps: acquiring domain feature data, calculating an initial domain risk level, and inputting a federated node local model for training to obtain a federated node gradient vector and an intermediate domain risk level; carrying out noise addition on the gradient through a personalized differential privacy technology, encrypting the gradient into an encrypted gradient vector by adopting a homomorphic encryption technology based on the Chinese remainder theorem, and transmitting the encrypted gradient vector to a federal coordination center; after decryption by the coordination center, personalized model parameters are generated through an aggregation mechanism based on cosine similarity and issued to each node, an optimized federated node local model is obtained through updating, and then an optimized field risk level is output and a governance decision is implemented according to the level. And calculating a strategy efficiency index in combination with strategy feedback index data and risk level variation, and dynamically adjusting a governance strategy to realize cross-domain data governance.

The application provides a power plant data security processing method, and belongs to the technical field of power Internet of Things security and privacy computing, which can at least partially solve the problems of complex certificate management of power plant monitoring system, large data aggregation calculation overhead and privacy leakage risk of cloud analysis in the prior art. The application comprises: generating a double-factor private key based on a certificateless public key cryptography system; serializing and encoding multi-dimensional operation data into a single integer using the Chinese remainder theorem; performing homomorphic encryption and signature on the encoded data using the double-factor private key, verifying the signature in batches on the edge side and aggregating in the ciphertext state; loading a neural network model adapted to homomorphic encryption on the cloud to perform ciphertext domain reasoning on the aggregated ciphertext; and decrypting the operation state analysis result on the authorized side. The application realizes ciphertext availability of power plant core data while ensuring data transmission integrity and confidentiality, and reduces communication and calculation overhead.

The present invention relates to the field of network data security technology, and discloses a ubiquitous network data security gateway that is resistant to quantum attacks, which includes a communication interface module, a verification module, a policy analysis module, an accumulator update module, a second signature module, and an output module. The verification module verifies the authenticity and member consistency of the signature based on the terminal public key and the accumulator public key; the policy analysis module dynamically filters fields according to predefined editable policies; the accumulator update module efficiently accumulates and witnesses subsets without calling private keys; the second signature module uses a lattice signature algorithm based on the SIS assumption and combines bounded rejection sampling to complete re-signing; the output module securely sends the re-signed data packet to the user; in addition, it also supports threshold sharding and Chinese remainder theorem reorganization to achieve distributed privacy protection and reliable recovery of highly sensitive fields. The present invention strikes a balance between quantum security and editability, and the re-signing and verification performance are controllable.

The present invention relates to a gradient aggregation federated learning method based on the combination of zero-knowledge proof and blockchain technology, which belongs to the field of distributed machine learning. By combining zero-knowledge proof (zk-SNARK) and scalable blockchain technology, the limitations of traditional methods in data privacy protection and model verification are broken through. The method uses zero-knowledge proof to verify the correctness of the global model, ensures the transparency and data privacy of the aggregation process, and introduces the Chinese remainder theorem to compress the proof, thereby reducing the storage burden of blockchain nodes. The hash value of the encrypted model update is recorded through the blockchain, and verification is performed based on the blockchain consensus node, which further improves data integrity and system transparency. In addition, the dynamic client selection mechanism introduced in the method optimizes participants based on training performance scores, thereby improving training efficiency and model quality. On the whole, the present invention provides a safe, efficient and transparent distributed learning solution.

An optimized encryption and decryption method and system based on an improved Paillier algorithm, comprising initializing parameters and initializing a secure noise pool using selected parameters and provably secure noise technology, reading plaintext and packing it, encrypting the packed plaintext using the selected parameters, the secure noise pool, an improved Paillier encryption scheme, and an improved Montgomery modular multiplication algorithm, mapping it to a Montgomery remainder domain, and performing modular multiplication acceleration calculation, finally mapping the Montgomery remainder back to the ciphertext domain to obtain ciphertext, decrypting the ciphertext using a Paillier decryption function to obtain the packed plaintext, and then performing an unpacking process to obtain the original plaintext. The present invention utilizes provably secure noise technology to generate a pre-calculated Paillier secure noise pool, accelerates the encryption algorithm based on the improved Paillier encryption scheme, accelerates the Paillier encryption and decryption algorithm based on the Chinese remainder theorem, and accelerates the Paillier ciphertext modular multiplication algorithm using an assembly-based improved Montgomery modular multiplication algorithm and a packing technology, significantly improving computational efficiency.

The present invention discloses a DNA storage method with composite code adjoint addressing coding. A composite code constructed from multiple pseudo-random sub-codes is used as an address sequence, which is adjointly coded and mapped with an error-corrected coded data bit sequence to combine and obtain long DNA fragments or short oligonucleotide molecules. During reading, the long fragment DNA is randomly fragmented or the oligonucleotide pool is read through next-generation high-throughput sequencing technology and demapped into two-layer bit sequences. Then, multiple pseudo-random sub-codes are used for sliding correlation capture of the sub-code period with the damaged composite code, and the unique address is determined by solving according to the Chinese Remainder Theorem. Finally, consensus and decoding are performed on the damaged data sequence. The method proposed by the present invention mainly solves the problems of large addressing difficulty, high assembly complexity, and DNA breakage when long fragment DNA in next-generation sequencing is randomly fragmented into short fragments, supports fast addressing and recognition of arbitrarily intercepted short fragments in shotgun sequencing of long fragment DNA, is also suitable for robust addressing of short fragments, and tolerates partial deletion of fragments, especially deletion at the beginning and end of the sequence.

A method, apparatus, and computer program product for privacy-preserving homomorphic inference using one-hot data representations. In the method, a client interacting with a cloud-based server submits a Chinese remainder theorem (CRT)-based one-hot mapping of a data element, and the server extends these mappings in an online phase to obtain a complete one-hot mapping of the element. After the server obtains the complete one-hot mapping, it performs an operation on the one-hot mapping under homomorphic encryption, such as a comparison operation associated with inference on the decision tree, and generates a result in response. The result is provided back to the client.

The application provides a mobile robot trajectory tracking system and method in a wireless packet loss environment, wherein in the wireless packet loss environment, current state information of the mobile robot is encoded and transmitted to a remote control terminal based on the Chinese remainder theorem and multi-description coding; the remote control terminal takes minimizing trajectory tracking error as a target, takes limited angular velocity of the mobile robot as a condition, generates optimal control instructions by using model predictive control according to input reference trajectory and reference angular velocity and current state estimation of the mobile robot obtained by wireless transmission and decoding, and encodes and transmits the optimal control instructions to an executing mechanism of the robot based on the Chinese remainder theorem and multi-description coding, so that the robot completes a desired trajectory tracking task in the wireless packet loss environment and the trajectory tracking error is minimized.

The application discloses a cross-domain data governance method and device based on federal intelligence, and relates to the technical field of federal learning. The method steps comprise: acquiring field characteristic data and calculating an initial field risk level, inputting a federal node local model to obtain a federal node gradient vector and an intermediate field risk level through training; adding noise to the gradient through individualized differential privacy technology, and then encrypting the gradient into an encrypted gradient vector through homomorphic encryption technology based on the Chinese remainder theorem and transmitting the encrypted gradient vector to a federal coordination center; after decryption by the coordination center, generating individualized model parameters through an aggregation mechanism based on cosine similarity and distributing the individualized model parameters to each node, updating to obtain an optimized federal node local model, and then outputting an optimized field risk level and implementing governance decisions according to the risk level; calculating a strategy performance index in combination with strategy feedback index data and a risk level change amount, dynamically adjusting the governance strategy, and realizing the governance of cross-domain data.

The present invention proposes a method and system for protecting the data of the entire life cycle of a smart grid. The method includes obtaining the data of the entire life cycle during the operation of the power grid, encrypting the power parameters based on a fully homomorphic encryption algorithm during the generation stage of the power parameters; and performing operations on the power parameters in the encrypted state; the encryption process includes: determining the public key and private key of the fully homomorphic encryption algorithm; and calculating a large number of power parameters based on the public key according to the Chinese remainder theorem to obtain a first intermediate plaintext; then randomly selecting a number of bit integers from the first intermediate plaintext to calculate a ciphertext. The method also includes decrypting the encrypted power parameters based on the private key of the fully homomorphic encryption algorithm during the use stage. Based on this method, a protection system for the data of the entire life cycle of a smart grid is also proposed. The present invention realizes data confidentiality throughout the entire life cycle and provides a data confidentiality support for the safe operation of the smart grid.

The invention provides a control method of a circuit breaker. A controller is bound with a circuit breaker body through a dynamic authorization mechanism. And when the controller is damaged or the service life is due, the controller can be independently replaced, and a new controller is re-paired with the original circuit breaker body through a cloud platform authorization process (sending an equipment information request authorization code, and writing the authorization code after validity verification), so that decoupling of the circuit breaker body and the controller is realized. Equipment information is verified through hardware features (equipment serial numbers, production dates and the like), the Chinese remainder theorem is adopted for compression, a Henon mapping chaotic system is adopted for generating a secret key matrix, and it is ensured that the equipment identity is unique and cannot be tampered. Therefore, the key defects of resource waste, weak safety mechanism, poor environmental adaptability, high operation and maintenance cost and the like caused by the fact that a traditional intelligent circuit breaker is not detachable can be overcome, and efficient utilization and safety management of equipment in the whole life cycle are achieved.