889 results about "Secret sharing" patented technology

The invention provides a user opinion privacy protection method and system based on federated learning and privacy difference, and relates to the technical field of privacy protection, and the method comprises the steps: a server receives a client request, divides a data set, and distributes the data set; the client performs local training by using a differential privacy machine learning algorithm, and disturbs model parameters by using Laplacian noise; the server uses secret sharing and homomorphic encryption technologies to aggregate parameters and update a global model; and the client receives the privacy protection strategy, carries out privacy processing on the user opinions and then sends the user opinions to the server for analysis. The method effectively protects user privacy and improves data utilization efficiency.

The invention discloses an edge cloud hierarchical collaborative task unloading optimization method fused with federal learning. According to the method, a three-level collaborative architecture of a terminal equipment layer, an edge node layer and a cloud center layer is constructed, and a task is split into a sub-task set containing a dependency relationship through a task analysis module. The edge node adopts a mixed model of a graph attention network and a double-delay depth deterministic strategy gradient, generates an unloading proportion in combination with an edge cloud topology and a real-time resource state, and realizes differential privacy protection through Laplace noise. In the federal learning process, the edge node only uploads Parel encryption parameters after local training, and the cloud generates a global meta-model through secret sharing aggregation and issues and updates the global meta-model. The multi-objective optimization model takes time delay, energy consumption and communication traffic as objectives, dynamically adjusts weight coefficients, and forms a'unloading-execution-learning-optimization 'closed loop. The method gives consideration to privacy protection and real-time performance, and is suitable for scenes with high requirements for privacy and timeliness.

The invention relates to the technical field of network security and edge computing, in particular to a trusted asymmetric encryption communication protocol of an edge computing gateway driven by a certificate chain, which comprises the following steps of: generating node characteristic data based on edge node hardware characteristics, generating dynamic certificate chain data through edge node cooperation, and recording the dynamic certificate chain data to a block chain to form global trust data; generating global random number data in combination with the dynamic certificate chain data and a chaotic mapping algorithm, and verifying the integrity of the global random number data; generating quantum initialization vector data in combination with the global random number data and the hardware noise data, and performing block encryption on the original communication data to generate block encrypted data; a secret sharing algorithm is used to distribute a dynamic session key to a highly trusted node to ensure the security of the key; and dynamically optimizing subsequent communication parameters according to a result of decrypting the communication data. According to the method, the security, robustness and adaptability of data transmission in an edge computing scene are improved by introducing a dynamic certificate chain, a chaotic mapping algorithm, block encryption and a feedback optimization mechanism.

The invention discloses a financial data processing method and system based on machine learning, and a storage medium. The method comprises the following steps: encrypting customer credit data of a financial institution through Paillier homomorphic encryption and extracting a risk feature vector; performing secret sharing segmentation on the local gradient parameters and then safely aggregating the local gradient parameters into global gradient parameters through a BGW protocol; on the basis of the privacy level, global gradient parameter differential privacy noise is injected and subjected to federal training to obtain a cross-institution credit evaluation result; calculating risk characteristics and evaluation results through homomorphic encryption to obtain an encrypted credit score, and performing secure multi-party calculation and decryption to generate a customer credit report; and block chain supervision compliance verification is carried out to generate an audit record, and a privacy budget optimization scheme is dynamically adjusted according to the business emergency degree. The technical problems that in an existing financial data processing method, information is incomplete due to data islands, data leakage risks are caused by insufficient privacy protection mechanisms, and an effective supervision compliance verification mechanism is lacked are solved.

Non-transitory computer readable storage mediums have instructions executed by processors to convert a first list at a first server into a first encrypted, permuted list with first dummy data elements and form a first encrypted linked list of pointers to locations in the first encrypted, permuted list. A second list at a second server is converted into a second encrypted, permuted list with second dummy data elements and a second encrypted linked list is formed of pointers to locations in the second encrypted, permuted list. Elements of the first encrypted, permuted list are combined with elements of the second encrypted, permuted list into a merged, sorted list of secret sharings, where the merged, sorted list of secret sharings is formed solely utilizing local computations at the first server, local computations at the second server and communications solely between the first server and the second server.

The invention relates to the technical field of data privacy and security protection, in particular to an educational data privacy security protection method based on a block chain and federated learning, and the method comprises the steps: dividing participating nodes into workers, verification committee and aggregation committee based on a dynamic role distribution mechanism of stock right weight, decentralized election is realized through Hash ring mapping; in combination with a double-layer privacy protection strategy of Diffie-Hellman key agreement and Shamir threshold secret sharing, counteractable differential disturbance is added to a local model, and verifiability of gradient exchange and noise elimination are ensured; a Byzantine detection algorithm is used, and poisoning attacks under non-IID data are effectively identified through gradient-based symbol clustering and similarity threshold filtering; based on a contribution degree incentive model of a block chain smart contract, the weight of the committee is dynamically adjusted through proven of interest (PoS), and Sybil attacks and centralized monopoly are prevented. By adopting the method, the effectiveness and privacy security of the education data in the distributed training process can be guaranteed.

The invention discloses a government affair data dynamic authorization management method based on secure multi-party computing, and relates to the field of government affair data security authorization management, and the method comprises the steps: distributing a unique identity identifier for each participant, generating an asymmetric key pair through employing a national secret SM2 algorithm, registering a public key and mechanism attribute information to an alliance chain smart contract, and generating an identity certificate package; and based on attribute information in the identity credential packet, the participants cooperatively generate anti-quantum dynamic attribute-based encryption key fragments through a secure multi-party computing protocol, and the anti-quantum dynamic attribute-based encryption key fragments are distributed to the participants by adopting a threshold secret sharing technology. Threshold decryption and token verification are achieved through an alliance chain verification intelligent contract, an authorization record is generated, an access control strategy of an edge computing node is configured according to the authorization record, an oblivious transmission protocol is adopted to respond to data query, and an audit node monitors an access log, dynamically adjusts attribute weight parameters and synchronizes the attribute weight parameters to a key fragment.

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

The invention provides a medical data sharing method and system based on multi-party security computing, and the method comprises the steps: carrying out the credible access control of participants through zero-knowledge proof and biological feature authentication, and enabling the participants to comprise a medical institution, a medicine enterprise / research institution, a patient and a supervision institution; after credible access control is passed, when a medical institution extracts patient data, k-anonymity, differential privacy and homomorphic encryption technologies are utilized to encrypt and desensitize the extracted patient data and store the data to a block chain; receiving a calculation task request and calculation parameters published on the block chain by a medicine enterprise / research institution, realizing mixed circuit and secret sharing mixed multi-party security calculation by a calculation node based on an ABY3 framework, and verifying the compliance of a calculation result; and receiving a result verification and auditing request of the supervision mechanism, and if the calculation result is verified to be within an authorization range through the smart contract, allocating rewards to the medical mechanism, the calculation node and the block chain platform according to a preset proportion, thereby effectively improving the security and timeliness of medical data sharing.

The invention discloses an unmanned aerial vehicle group distributed management method based on a mobile active secret sharing technology, which supports off-line of a trusted institution and comprises the following steps: the trusted institution TA generates public parameters; a mobile base station MS and an unmanned aerial vehicle UAV participating in communication respectively register with a trusted mechanism in a registration stage, and acquire information such as a secret key and a certificate; the UAV joins the MS and is administered by the MS, and after mutual identity authentication, the MS distributes secret shares to the UAV; performing identity authentication on the unmanned aerial vehicle group; the unmanned aerial vehicles of the two groups share the share, group fusion is achieved, and after a new share is obtained, each unmanned aerial vehicle updates the certificate of the unmanned aerial vehicle. According to the method, the sub-secrets of the unmanned aerial vehicles are autonomously updated through a mobile active secret sharing technology, and fusion of completely decentralized unmanned aerial vehicle groups is realized. Secondly, an efficient certificate self-updating method is designed. The unmanned aerial vehicle can update the certificate only by calculating a threshold signature. Detailed safety certification and comprehensive experiments show that dynamic autonomous management of the distributed unmanned aerial vehicle group can be realized, and the method has good safety characteristics and relatively low calculation overhead.

The invention relates to an alliance chain identity privacy protection method and system based on multi-level group signature and distributed key management, and belongs to the field of block chain technology, network and information security. According to the method, a multi-level group signature structure is adopted, anonymous identity verification is achieved in the transaction process, privacy protection is further enhanced through zero-knowledge proof, anonymous identity verification is achieved in the transaction process, it is ensured that privacy of participants is not leaked, a homomorphic encryption algorithm is used in the signature and verification process of transaction data, and the transaction data are subjected to identity authentication. And privacy leakage is prevented. And meanwhile, the Shamir secret sharing algorithm divides the master key and stores the master key in a plurality of sub-group members in a distributed manner, so that the anti-attack capability and the key security are enhanced. According to the method, a dynamic group member management and double signature verification mechanism is further introduced, so that the flexibility and the overall security are improved. The method has significant advantages in the aspects of identity anonymity, data integrity and efficiency, and is suitable for alliance chain application scenarios with high privacy and security requirements.

The invention discloses an efficient secret state joint neural network inference method. The method comprises the following steps: S100, a data owner C and a model owner # imgabs0 # respectively send privacy data and a privacy model to computational nodes # imgabs1 # and # imgabs2 # in a secret sharing manner; s200, computing nodes # imgabs3 # and # imgabs4 # to run a secret state joint neural network reasoning algorithm, and respectively calculating secret shares Z0 and Z1 of reasoning results by sequentially executing secret state computing layer protocols, the secret state computing layer protocols comprising: S210: a secret state convolution layer algorithm # imgabs5 #; s220, a function layer algorithm # imgabs6 # is activated in a dense state; the invention further discloses an efficient dense state joint neural network inference system. According to the technical scheme, the ReLU algorithm with few communication rounds is designed based on the function secret sharing technology, so that the communication cost required for calculating the activation function is reduced, the convolutional neural network inference sub-protocol is designed by utilizing bilateral comparison and correct symbol discrimination, the inference accuracy is improved, and the inference result is consistent with a plaintext inference result.

The invention belongs to the field of passwords, and discloses an anti-quantum threshold digital signature method and system capable of tolerating high network delay. The method comprises the following steps: in a secret key generation stage, a trusted third party randomly selects a secret key and performs Shamir secret sharing on the secret key, and distributes a secret sharing value to each signer; in a distributed signature stage, each signer carries out packaging and secret sharing on a secret sharing value, a proving sub-circuit of a public key is operated based on a secure multi-party computing protocol, and each participant outputs a signature through two rounds of interaction. The anti-quantum threshold digital signature scheme has function interchangeability, that is, the signature generated by the threshold scheme and the signature generated by the original signature scheme can be verified by the same verification algorithm; meanwhile, the threshold digital signature scheme is efficient and achievable, and a threshold signature protocol in a scene of two parties of a wide area network only needs 2 seconds; moreover, the method has a better number of rounds, and the signature algorithm only needs two rounds.

The invention provides an intelligent credit product recommendation method and system based on multi-source data fusion, and the method comprises the steps: carrying out the feature extraction of multi-source credit data, and obtaining a feature vector set; performing data fusion on each feature vector in the feature vector set to obtain fused feature data; performing homomorphic encryption on the fused feature data to obtain homomorphic encrypted data, and storing the homomorphic encrypted data in each security node; performing similarity calculation and clustering operation in a ciphertext space through a secret sharing protocol based on each security node to obtain an encrypted clustering result; and decrypting the encrypted clustering result, and matching a decryption result with the credit product to obtain an intelligent recommendation result of the credit product. According to the method, feature extraction is carried out on multi-source credit data, and fusion is carried out; and in combination with homomorphic encryption, the defects that the current credit product recommendation method is easy to leak privacy and cannot comprehensively and accurately evaluate the credit status of the customer are overcome.

The invention relates to the technical field of information retrieval, and provides a privacy information retrieval system and method based on a block chain and function secret sharing, and the method comprises the steps: carrying out the encryption and keyword extraction of a data document; generating a Bloom filter index table between the keyword and the document based on the keyword trap door; uploading the encrypted file and the Bloom filter index table to a DSSP end, and transmitting the hash value of the encrypted file and the Bloom filter index table to a block chain for on-chain storage; storing the encrypted file in a distributed storage node under the chain according to the divided share; and the block chain calculates data of each column of the Bloom filter index table through consensus to obtain a message verification code, and the message verification code is stored on the block chain. According to the method, the index is constructed through symmetric encryption and the Bloom filter, and block chain evidence storage and FSS distributed storage are combined, so that data privacy protection and index credibility are realized. Through verification and tampering prevention, the problem that the existing FSS lacks verification and auditing mechanisms is solved.

The invention discloses a key sharing and security detection scheme based on an intelligent electric meter, and aims to solve the problems that an untrusted electric meter in an intelligent power grid is difficult to identify effectively, the detection scale is uncontrollable and the communication security is insufficient. According to the scheme, the elliptic curve cryptography, the threshold secret sharing mechanism and the physical unclonable function are combined, and hardware-level binding of the unique identity of the equipment and the secret key is achieved in the registration stage. Through a threshold password mechanism, a plurality of intelligent electric meters cooperatively participate in key reconstruction and encryption communication, and the intelligent electric meters can still work normally when part of the electric meters fail or are broken through. The center node can actively identify a fault or a malicious ammeter and dynamically adjust a communication strategy according to the integrity and correctness of the feedback information. Meanwhile, the scheme supports dynamic identity updating and integrity verification, and effectively resists modeling attacks, Sybil attacks, replay attacks and DoS / DDoS attacks. According to the invention, secure identity authentication, reliable key distribution and efficient anomaly detection are realized, and the security of smart grid terminal communication is improved.

The invention belongs to the technical field of information security, and particularly relates to a super-threshold data set intersection method and system for security information processing. The method comprises the following steps: S1, carrying out casual key value pair storage OKVS encoding and decoding between each participant and other participants; s2, each participant constructs a hash table according to a decoding result and elements of the participant; and S3, sending the constructed hash table to a specified party, summarizing information in the hash tables of all participants by the specified party, and finally obtaining a super-threshold intersection result by using a secret sharing scheme. The method has the characteristics that the hardware and operation and maintenance cost can be reduced, the data security is enhanced, and the calculation efficiency is improved, so that the industrial control requirement of short-time response is met.

A method for operating a data analytics system includes storing, at a first server system of the data analytics system, a first key associated with a data provider and / or storing, at a second server system of the data analytics system, a second key associated with the data provider. The first key and the second key are complementary keys generated using a secret sharing based cryptographic algorithm based on a policy arranged to control usage of data provided by the data provider. The first key and the second key are arranged to facilitate performing of a data analytics operation at the data analytics system.

A method of performing a threshold digital signature of a message, the method comprising: receiving, at a signing entity, one of a plurality of private signing keys and a public verification key, wherein each of the plurality of private signing keys is associated with the public verification key and the public and private keys are generated using a lattice-based signature scheme; computing a first commitment and transmitting the first commitment to each of a plurality of remote entities; receiving a commitment from each of a subset of the plurality of remote entities; computing a first partial signature using the received commitments and the first commitment, the received private key, and the message, wherein the computation of the first partial signature includes performing a linear transformation using a polynomial vector threshold secret sharing scheme, PVSS, on the commitments and combining the transformed commitments; transmitting the first partial signature to each of the subset of remote entities; receiving a partial signature from each of the subset of the plurality of remote entities; and computing a combined signature using the computed first partial signature and the received partial signatures.

Systems and methods for secure peer-to-peer communications are described. Devices registered into trusted network may be capable of establishing a shared data encryption key (DEK). In embodiments, each device may be configured to obtain a share of a data encryption key (DEKi) that can be stored locally. The shares may be shares in an M of N Secret Sharing Scheme. This may involve a network that includes an integer, N, devices, and in which M devices may share a secret (i.e. the DEK) during communications, M being an integer less than or equal to N. To obtain the entire DEK during encryption / decryption, a requesting device may send requests to M of N devices for their shares of the DEK. Once M shares are obtained, they may be used generate the DEK for encrypting / decrypting data between the devices.

The invention discloses a federal learning security training method and system based on differential privacy, belongs to the technical field of artificial intelligence, and aims to solve the technical problem of how to realize data privacy protection and model precision balance in cross-mechanism model training. Comprising the following steps: constructing a distributed structure comprising a plurality of clients and a server; each client constructs a noise variance calculation model by taking the gradient feature, the privacy budget coefficient, the data sensitivity level coefficient and the training stage coefficient as calculation parameters after each round of local training is finished, and Gaussian noise is calculated according to the noise variance; verifying the noise variance of each round, and adjusting the calculation parameters of the noise variance based on the comparison result of the accumulated budget consumption and the global privacy budget; dynamically allocating the data sensitivity level of the local training data and the budget allocation proportion of the client; and the server performs secure aggregation through a secret sharing algorithm, and distributes the updated global model parameters to each client.

The invention provides a decision tree security reasoning method and framework based on an efficient element selection protocol, and belongs to the technical field of data security processing. According to the method, nodes and user attributes of a decision tree are converted into two-dimensional matrix representation from one-dimensional vectors, and a constant round communication conversion protocol is designed based on function secret sharing, so that a ciphertext selection index is converted into two ciphertext one-hot vectors; and performing ciphertext dot product operation on the two-dimensional matrix and the two one-hot vectors to complete an element security selection function. After a one-dimensional vector is converted into a two-dimensional matrix, through ciphertext dot product operation, the communication size is not directly proportional to the number of nodes and the number of attributes any more and is only directly proportional to the square root of the number of elements. According to the method, a secure dot product and function secret sharing technology based on secret sharing is combined, the communication size is reduced to be in direct proportion to a square root from being in direct proportion to the number of nodes and the number of attributes, communication and calculation expenses are remarkably reduced, and an efficient privacy protection decision tree reasoning framework is provided.

The invention relates to a distributed identity-based ring signature algorithm supporting malicious termination resistance and suitable for a block chain, which is characterized in that a threshold identity-based ring signature algorithm, a Joint-Shamir-RSS secret sharing algorithm, a KZG commitment algorithm and an information theory message verification code (IT-MAC) technology are fused. A threshold identity-based ring signature generation process and an anti-malicious termination function without participation of a trusted third party are realized. A main public key of a ring is generated by using a public key aggregation method, and safe and secret sharing of main and private keys is realized by combining a Joint-Shamir-RSS secret sharing algorithm and a KZG commitment algorithm, so that dependence on trusted KGC is eliminated; by introducing IT-MAC into a threshold identity-based ring signature algorithm, a data uploading node can effectively check the validity of a part of signatures generated by an assisting node, so that the function of resisting malicious termination is realized. The distributed signature scheme not only can provide an additional privacy protection function for a signer, but also has the capability of effectively resisting malicious termination, has higher security, and is suitable for being applied to a block chain system.

The invention relates to the technical field of power system frequency modulation control, in particular to a thermal power generating unit collaborative frequency modulation method and system based on block chain federated learning. According to the method, a decentralized P2P network is constructed through a block chain technology, and model parameters are initialized based on a secret sharing mechanism; carrying out local training by adopting an adaptive federal near-end optimization algorithm, measuring data isomerism through KL divergence and dynamically adjusting a regular coefficient; carrying out noise addition on a sample by adopting differential privacy, and carrying out homomorphic encryption to realize parameter encrypted transmission; selecting representative nodes based on a block chain consensus mechanism to execute parameter aggregation in the encryption domain; and multi-unit collaborative frequency modulation is realized through model prediction control. According to the method, the problems of data privacy protection, heterogeneous data adaptation and decentralized cooperative training are solved, and the stability of power grid frequency regulation and control is improved.

The invention provides a distributed function secret sharing key generation method aiming at the problems that an existing secret sharing key generation scheme depends on a trusted third party and does not support limitation of arithmetic sharing operation. The invention provides a solution for efficient distributed key generation based on improved function secret sharing between two communication parties. The protocol designed by the invention supports arithmetic sharing input and output, the calculation overhead and the communication overhead in the distributed key generation process are greatly reduced by optimizing the communication process on the premise of ensuring the safety and the accuracy of calculation, and the requirement on a trusted third party is completely removed by designing an efficient two-party calculation 2PC protocol, so that the communication efficiency is improved. A participant is allowed to directly generate keys for a distributed point function (DPF) and a distributed comparison function (DCF) through a two-party calculation protocol, the security and practicability of key generation are remarkably improved, and the method is particularly suitable for a scene without a trusted third party.

The invention discloses a rational entrustment federated learning method and system based on differential privacy, and the method achieves the purpose that a client controls the expected income of a server through constructing a rational calculation model based on a zero determinant strategy and establishing a linear income relation between the server and the client, and further achieves the purpose that the client controls the expected income of the server through a bounded differential privacy protection mechanism. And finally, whether the servers execute correctness aggregation or not is checked through an aggregation result verifiable algorithm of differential privacy based on secret sharing, meanwhile, offline of a certain number of servers can be tolerated, the influence of network abnormality, power failure and other emergencies on training can be weakened, and the training efficiency can be improved. The technical problem that the normal operation of model training in federated learning still cannot be ensured because only the aggregation result of the server can be checked in the existing research and the correct aggregation operation of the server is not considered is solved.

The invention provides a privacy protection multi-task allocation method for an unmanned aerial vehicle crowdsourcing perception system, which combines addition secret sharing and homomorphic encryption to realize bilateral privacy protection of a task side and an unmanned aerial vehicle position. The task requester and the working party split a task position and a UAV departure position into two secret shares [.] 1 and [.] 2 by adopting an additive secret sharing mechanism respectively, and send the two secret shares [.] 1 and [.] 2 to the two independent service parties S1 and S2 respectively; the service party calculates an encrypted square Euclidean distance between the UAV and the task based on the shared share, and generates two distance matrix shares D1 and D2. On the basis, the two service parties cooperatively execute privacy comparison and a minimum index protocol under the optimized Paillier, and multi-task encryption shortest path distribution is realized in combination with a Hungary algorithm. According to the method, addition secret sharing is fused, Paillier encryption and task matching optimization are optimized, the total flight path of the UAV is remarkably reduced while position information privacy of the whole task allocation process is guaranteed, and good safety and deployability are achieved.

A distributed re-encryption apparatus comprises: a distributed re-encryption key storage part that stores shares obtained by secret-sharing a re-encryption key that re-encrypts a ciphertext into one encrypted with a different encryption key without decrypting the ciphertext; and a distributed re-encryption part that re-encrypts using the shares of the re-encryption key the ciphertext into one encrypted with a different encryption key without decrypting the ciphertext.

Examples relate to machine readable storage storing instructions arranged, when processed, to realise a cryptographic machine readable instructions for signing a message; the instructions comprising: instructions to receive, from a plurality of participating devices of a set of devices, a threshold number of shares of a private key, sk; the shares having been created using a (t,n)-threshold secret sharing scheme, where n>=t and t>n / 2; instructions to receive respective state indicia from the plurality of participating devices; the respective state indicia being indicative of the number of messages having been signed using the private key, sk; instructions to recover the private key, sk, using the received shares; instructions to sign a message using a hash-based signature scheme subject to assessing a state indicium indicating the highest number of messages that have been signed using the private key. sk; and instructions to establish a state indicium indicating the highest number of messages, m, that have been signed using the private key, sk.

The embodiment of the invention provides a secret sharing and packaging method and device. And the plurality of participants respectively encode vectors formed by secret sharing of k pieces of data owned by the participants in a specified domain space to respectively obtain first domain elements owned by the participants, and the first domain elements have data structures meeting addition homomorphism. Then, the multiple participants perform secret sharing addition operation based on first domain elements owned by the multiple participants through first data interaction based on secure multi-party calculation, so that the multiple participants respectively obtain secret sharing of first sum values of the first domain elements owned by the multiple parties; the secret sharing of the first sum value is used as the secret sharing of a second domain element obtained by coding a vector formed by k data in a directional domain space.