299 results about "Secret share" patented technology

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 a distributed key generation method and device based on an SM2 algorithm, a medium and equipment. The method comprises the following steps: determining a class group encryption key, a class group decryption key and a corresponding first zero knowledge proof through public parameters generated based on the SM2 distributed key; each participant shares respective secret share based on the class group encryption key, the class group decryption key and the first zero-knowledge proof, and creates a second zero-knowledge proof indicating that sharing is correct; each parameter party collects honest distribution shares and decryption shares based on the second zero knowledge proof, calculates a part of private keys and a part of public keys according to the decrypted secret shares, and creates a third zero knowledge proof indicating correct decryption; according to the third zero knowledge proof, partial public keys of participants correctly executing decryption operation are determined to reconstruct a global public key, the secret is shared by using a polynomial, each participant can contribute a part of shares, and a distributed secret key is generated without any credible setting.

The invention relates to an anti-quantum distributed asynchronous random beacon method and system. The method comprises: a distribution stage of executing an anti-quantum asynchronous verifiable secret sharing method; an asynchronous common subset protocol is executed, distribution nodes corresponding to received effective secret shares serve as input, and a node set i with the size of t is consensus; executing a reconstruction stage of the anti-quantum asynchronous verifiable secret sharing method, reconstructing the secret value of each node in the set I, and if the reconstructed secret value is invalid, rejecting the node from the set I; and outputting the XOR sum of the secret values of the nodes in the set I as a public random number. According to the method, distributed generation of public random numbers is supported, the single-point fault problem is avoided, the system security can be ensured in an asynchronous network, and quantum computer attacks can be resisted.

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.

The invention discloses an identity authentication method and system based on a national secret algorithm, and the method comprises the steps: building a hierarchical key management system based on a national secret IBE framework, generating a system master key pair through employing an SM2 algorithm, and achieving a decentralized key distribution mechanism; constructing a domain perception differential privacy protection module, defining a privacy budget allocation strategy according to the security level, and adding calibrated Laplace noise to the user identity feature vector; designing a distributed batch matrix multiplication protocol, and decomposing the distributed batch matrix multiplication protocol to a plurality of computing nodes for parallel processing through a secret sharing technology; a zero-knowledge proof verification mechanism is implemented, and identity verification is completed through a commitment scheme based on an SM3 hash algorithm; deploying a self-adaptive key updating strategy, and analyzing threat level change through a threat situation evaluation function; and establishing a secure communication channel based on SM4 symmetric encryption, and performing encryption processing by using the temporary session key. The security and expandability of the system are improved, the privacy of the user is effectively protected, and the system adapts to a dynamically changing network threat environment.

Methods and systems for securely generating secret shares in a distributed manner and distributing those secret shares to cryptographic devices are disclosed. The cryptographic devices can subsequently use these secret shares to perform threshold distributed cryptographic operations (such as encryption or decryption). A threshold number of generating cryptographic devices can each generate their own secret shares. These devices can also each generate partial secret shares that can be combined by receiving cryptographic devices to generate their own respective secret shares. Additionally, the generating devices can generate commitments corresponding to their secret shares. The generating devices can transmit the commitments to the other cryptographic devices and the partial secret shares to their corresponding receiving devices. At a later time, cryptographic devices possessing at least a threshold number of secret shares can collectively perform cryptographic operations using those secret shares.

The sender stores a pair of sender's public and private keys and a public key of the receiver, and carries out the steps of:A—generating a master key, that is a secret shared with the receiver, by key derivation from a current root key and using the sender's private key and the receiver's public key, and updating the root key with the generated master key;B—generating, by key derivation from said master key, a chain of message keys for securing messages to communicate to the receiver;C—generating a next pair of sender's public and private keys, sending the next sender's public key to the receiver and executing again the steps A andB using the next sender's private key and the same receiver's public key;wherein the current root key used in the step A isat a first iteration of step A, an initial root key prestored in the sender, said initial root key being a secret shared with the receiver, andat each subsequent iteration of the step A, the root key that has been updated at the preceding iteration of step A.

The embodiment of the invention discloses a safety calculation method and device for robot cluster collaboration and a medium, and relates to the technical field of safety calculation, and the method comprises the steps: carrying out the participant authentication of a robot cluster and a production enterprise node in advance, and carrying out the dynamic identity verification of each robot after the participant authentication is passed, the operation feature data of each target robot passing verification are extracted and encrypted, and encrypted feature vectors are determined; splitting the encrypted feature vector into a plurality of data fragments, storing the data fragments to a distributed node, obtaining a predetermined task cooperation strategy, and distributing the task cooperation strategy to an edge computing node in a secret sharing manner; executing safety calculation in a ciphertext state through a task cooperation strategy and the plurality of data fragments, determining a joint motion control instruction of each target robot, and generating corresponding zero-knowledge proof data; and after the verification is passed, the encrypted control instruction is distributed through the block chain smart contract, so that safety calculation of robot cluster collaboration is realized.

The invention discloses a privacy protection neural network reasoning method based on multi-point evaluation. According to the method, in the reasoning process of the privacy protection neural network, a given nonlinear function is constructed into a K-segment k-degree polynomial, a safe multiplication tree and a safe remainder tree are established, and then the remainder polynomial is safely evaluated. Due to the fact that the polynomial power needing to be evaluated in the online stage is reduced, the number of self-multiplication terms is reduced, the number of communication rounds of overall polynomial evaluation is reduced, the number of calling times of a secure multiplication triple in secret sharing is reduced, and the overhead of offline pre-calculation is correspondingly reduced. In addition, the hierarchical structure of the secure multiplication tree and the remainder tree supports multi-point input parallel computing, and the parallel computing capability of a modern multi-core processor or a GPU can be fully utilized.

Embodiments are directed to secure configuration change at an edge device. A method includes receiving configuration change data at a device, the configuration change data associated with an encrypted authentication key; sending the configuration change data to a plurality of peer devices; receiving secret shares from a quorum of the peer devices, wherein each of the quorum of peer devices sends its respective secret share if it determines that the configuration change data complies with a configuration policy; constructing an decryption key using a quorum of the secret shares; decrypting the authentication key using the decryption key; and applying the authentication key to install the configuration change on the device. The method may further comprise determining, by the device, whether the configuration change data complies with the configuration policy; and constructing the encryption key using the quorum of the secret shares and a secret share stored on the device.

The invention discloses a multi-party cooperative charging load safety prediction method and system capable of resisting malicious behaviors, and the method comprises the steps: enabling a trusted third party to generate a global authentication key, a function key and a related random value, which are needed in a load prediction process, at an offline stage in a system initialization stage; the data owner splits the original power data into a plurality of parts and sends the parts to the server; the charging operator decomposes the load prediction model into a plurality of secret shares, and the secret shares are deployed on different server nodes respectively; the plurality of server nodes cooperatively execute a safety function protocol, complete a neural network reasoning process and send a load prediction result share to a power grid dispatching center; and the power grid dispatching center reconstructs the received load prediction result share to obtain a load prediction result. The method can support a plurality of participants, greatly reduces the calculation and communication overhead under the condition of guaranteeing high prediction precision, and can resist malicious behaviors of server nodes.

The invention relates to the technical field of federated learning, in particular to a federated learning security aggregation method based on vector space secret sharing, which comprises the following steps that: a client divides a local model gradient into a plurality of secret shares and distributes the secret shares to a plurality of servers; the server carries out aggregation operation on the secret share through a security computing protocol, wherein the aggregation operation comprises addition and multiplication operation; calculating the similarity between the clients based on the secret state data, and screening out a credible client set; and executing security aggregation on the gradient share of the trusted client, reconstructing a global model gradient and issuing the global model gradient. According to the method, client poisoning attacks can be resisted, server reasoning attacks can also be resisted, a federal learning global model security aggregation method is designed based on vector space secret sharing, and threats caused by server offline are reduced.

The invention provides a block chain privacy protection method and system based on dynamic threshold homomorphic encryption, and efficient encryption and flexible management of privacy data are realized by combining a Paillier semi-homomorphic encryption algorithm and a dynamic threshold secret sharing mechanism. The method comprises the following steps: generating a public key-private key pair and a threshold parameter set based on a large prime number, carrying out grouping encryption on privacy information to be protected, directly executing dynamic data updating in a ciphertext state by utilizing an addition homomorphic characteristic, then splitting a decryption key into share ciphertexts, and realizing decentralized key distribution and security recovery through threshold parameter constraint; for a participant adding or exiting event, a threshold parameter set is dynamically adjusted and a key rule is reconstructed, and an encrypted data set is synchronously updated to maintain consistency. Therefore, the flexibility and expandability of the block chain system are improved while the account book privacy and the network privacy are guaranteed.

A computer-implemented method of generating shares of a shared secret, wherein each of a group of participants has a respective first secret share of the shared secret, wherein the method is performed by a first participant of the group and comprises: generating a respective blinding share of a shared blinding secret, obtaining at least a threshold number of respective intermediary shares from each of the first group of participants, wherein each respective intermediary share is generated based on a respective blinding share and a respective first secret share; generating an intermediary value based on each of the obtained intermediary shares; and generating a respective second secret share of the shared secret, wherein the respective second secret shared is generated based on the intermediary value and the respective blinding share.

The embodiment of the invention discloses a federated learning method and device for a low earth orbit satellite network and electronic equipment. A specific embodiment of the method comprises the following steps: sending an initial global parameter to each participating satellite through a ground station; for each participating satellite, the following steps are executed: generating trained parameters based on local data collected by the participating satellite, initial global parameters and a preset model; performing secret sharing on the trained parameters to obtain a secret share parameter set; sending each secret share parameter to each aggregation satellite based on a preset safe path set; for each aggregation satellite, performing weighted summation on the secret share parameter from each participating satellite to obtain a weighted secret share parameter, and sending the weighted secret share parameter to a ground station; global training parameters are generated through the ground station according to the received weighted secret share parameters. According to the embodiment, the practicability and safety of federated learning in the satellite network are improved.

Systems and methods are disclosed herein for protecting data in a storage device by encrypting or decrypting the data with a Data Encryption Key (DEK). The storage device is communicatively coupled to a host and is locked with the host by secret sharing. In one example, the storage device comprises a Physically Unclonable Function (PUF) configured to, during a key generation phase of operation, generate a set of DEK responses based on a set of DEK challenges (chalDEK) and an assembler configured to obtain a set of SED DEK secret shares (SSSED) based on the first set of DEK responses, receive additional data, and assemble at least the set of SED DEK secret shares (SSSED) and the additional data to create a DEK master secret. The storage device also comprises a crypto module configured to receive a DEK based on the master secret and perform encryption and / or decryption of data using the DEK.

This invention discloses a privacy-preserving method and apparatus for multi-party longitudinal logistic regression based on secret sharing. The method involves a coordinator generating a large number of Beaver triples and distributing them to all participants before the protocol begins. First, model weights are allocated to each participant using secret sharing technology. Then, each participant collaboratively calculates the forward propagation value cross terms. Next, based on their respective datasets, model weight slices, and secret slices of the forward propagation value cross terms, the output value is obtained, and the active party calculates the final forward propagation value. Then, the active and passive parties collaboratively calculate the model gradient cross terms and obtain the secret slices of the model gradient cross terms, and then locally update the model weight slices. Because this invention generates a large number of Beaver triples and distributes them to each participant before the protocol begins, the communication and computational workload can be shifted to before the protocol starts. Furthermore, secret slicing can be performed among multiple participants, thus allowing for expansion to three or more participants.

The invention provides a multi-person approval control method, an electronic device, a readable medium and a program product, and the method comprises the steps: responding to the submission of an approval application, generating a process continuing key for the approval application, splitting the process continuing key into n secret shares through a threshold secret sharing algorithm according to a preset (k, n) threshold parameter, and distributing the n secret shares to each approver; receiving an approval instruction submitted by each approver and the signed secret share associated with the approval instruction; verifying the validity of the signed secret share of which the approval instruction is agreed, and determining the signed secret share as an effective share if the verification is passed; when the number of the effective shares reaches or exceeds k, at least k shares are selected from the effective shares, and a process continuing key is restored through a threshold secret sharing algorithm; and performing comparison verification on the restored flow continuing key and a flow continuing key generated during initialization, and triggering execution of a business flow corresponding to the approval application after verification is passed. According to the invention, multi-person examination and approval can be realized, and compulsory compliance and tampering prevention

A method for implementing distributed key generation in a blockchain by a blockchain node includes: generating n secret shares, retaining a share and respectively encrypting a remaining n−1 secret shares by using keys of receivers, generating a public verification parameter corresponding to a secret share of the blockchain node, generating a zero-knowledge proof indicating that the secret share of the blockchain node and the public verification parameter match, sending the secret share, the public verification parameter, and the zero-knowledge proof to an on-chain contract by using a transaction, verifying, by the on-chain contract based on the zero-knowledge proof, that the encrypted secret share and the public verification parameter match, obtaining, from contract information, a verified secret share corresponding to the blockchain node, performing decryption by using a key of the blockchain node, and calculating a private key share of the blockchain node based on a local secret share.

The present invention discloses an SM2 threshold signature system based on dynamic secret sharing, which relates to the field of information security technology. The system includes: an initialization module, a distributed key generation module, a signature module and a verification module; the initialization module is used to initialize public parameters; the distributed key generation module is connected to the initialization module, and is used to generate a secret share based on the initialized public parameters; the signature module is connected to the distributed key generation module, and is used to generate a signature pair based on the public parameters and the secret share; the verification module is connected to the signature module, and is used to verify the signature pair. In view of the fact that the existing SM2 threshold signature algorithm cannot use the original signature private key to ensure that the external signature public key remains unchanged when the number of participating users needs to change or the threshold value changes, the present invention uses a distributed key generation module to generate a secret share, which can dynamically add or delete the threshold value and the number of participating users under the premise of ensuring that the original signature private key remains unchanged.

The invention discloses a sensitive data security storage method based on image information hiding, which comprises the following steps: encrypting information M to be hidden by using a key K to obtain a ciphertext C; encrypting the key K to obtain an encryption key EK, decomposing the encryption key EK into a master secret share and a recombined secret share, and decomposing the recombined secret share into n-1 secondary secret shares; hiding the master secret share, the ciphertext C and a randomly generated random value R in the image; and respectively storing the n-1 second-level secret shares and the key expiration time T at n-1 users in the system. According to the method, the hierarchical linear secret sharing technology and the image information hiding technology are combined, the security of sensitive data storage can be improved, a user can extract information from the image only by using a password, the method is not limited by certain specific equipment, and the operation convenience is high.

The invention discloses a non-interactive digital identity authentication method and system for privacy outsourcing calculation, and the method comprises the steps: a user mobile terminal analyzes an identity certificate of a user into a witness vector and generates a secret share, selects an authentication node, generates and transmits an anchor point secret share, a witness vector secret share and a label for the authentication node, and transmits the anchor point secret share, the witness vector secret share and the label to the authentication node; sending a global key secret share and a local key component secret share for generating a tag to the remaining computing nodes; each computing node in the privacy computing cloud cluster performs witness consistency check, if the check is passed, an identity authentication circuit is executed in a secret state to obtain a secret share of an authentication result, and a proof fragment of a simple non-interactive zero-knowledge proof is calculated based on a calculation track executed by the circuit; the authentication nodes gather to obtain a complete proof and recover an authentication result, the proof is delivered to a verification party, the authentication result is pushed to a user mobile terminal, and in the proof generation process, PIOP consistency check needs to be carried out after each round of polynomial commitment is generated.

The invention belongs to research in the field of privacy protection multi-party data collaboration, and particularly relates to a multi-party manifold learning method based on secret sharing. The method comprises the following steps that: a plurality of data owners firstly distribute copy secret shared shares of respective data sets to three computing servers; each computing server interactively computes a k-nearest neighbor distance matrix of all sample pairs on the secret share of the data set based on a novel secure top-k algorithm; then, each computing server interactively computes the distance of a full-source shortest path on the secret share of the k-nearest neighbor distance matrix by adopting a low-round Floyd-Warshall algorithm; and finally, each computing server performs secure multi-dimensional scaling on the shortest path distance matrix shared by the secret to obtain low-dimensional embedding of the data set, and any two servers send the secret share of the low-dimensional embedding to a specified user to locally recover the secret share into a plaintext. According to the invention, the number of distance calculation is reduced, and an efficient and safe top-k and all-source shortest path algorithm is provided.

The invention relates to the field of energy data analysis, in particular to an energy big data monitoring method and device based on privacy computing, and the method comprises the steps: sending a task request to a plurality of data parties, and then responding to the data authorization of the data parties for the task request; the method comprises the following steps: establishing a cooperative computing network and a secret sharing interface model for a data party sending data authorization, obtaining multi-dimensional energy data in the cooperative computing network through the secret sharing interface model, and then carrying out joint statistical operation on the multi-dimensional energy data based on a preset joint statistical task to obtain a joint statistical result. Compared with the prior art, the method provided by the invention realizes the real-time performance of data transmission on the basis of ensuring the safe transmission of the energy data.

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.

This invention provides a privacy-preserving community search method and system for graph data streams. It utilizes a secret shared domain comprised of multiple servers. Within this domain, each server can only access the first encrypted data of the graph data stream's list structure and the second encrypted data of the search parameters. Throughout the community search process, the search parameters and all information in the graph data stream except for the time of generation are processed within the encrypted domain and are not leaked to the querying server, thus achieving privacy protection during the community search process for graph data streams.

This invention discloses a password matching method based on equality testing. Each matching server obtains a login password secret share; the difference between the pre-held registration password secret share and the login password secret share is obtained to get a difference secret share; the first equality test problem between the registration password secret share and the login password secret share is transformed into a second equality test problem between the difference secret share and 0; based on addition, multiplication, and inner product calculations under replicated secret sharing, the second equality problem is subjected to ring dimensionality reduction to obtain a third equality test problem; the third equality test problem is solved based on Fermat's Little Theorem to obtain the equality test result, thereby obtaining the password matching result.

The present invention discloses a decision tree product recommendation method based on two-party secure computing, which can be applied to data holders or model holders. The method includes: obtaining a secret sharing of the decision tree root node index and a lookup table; obtaining a secret sharing of the node information of the corresponding node on the decision tree through a selection protocol, thereby obtaining a secret sharing of the corresponding eigenvalue index, and obtaining a secret sharing of the corresponding eigenvalue through a lookup table; comparing the eigenvalue and the threshold through a conditional oblivious transfer protocol, thereby selecting a left subtree node index or a right subtree node index; based on the secret sharing of the selected node index, obtaining a secret sharing of the node information of the corresponding node on the decision tree through a selection protocol, thereby obtaining a secret sharing of the corresponding classification value, updating the secret sharing of the product recommendation result based on the secret sharing of the classification value, traversing the decision tree until a predetermined number of nodes are traversed to obtain the final product recommendation result.

The application discloses a model parameter aggregation method and system based on flow security multi-party computation, terminal equipment and medium, relates to the technical field of federated learning, and is applied to a server and a client which is provided with an exit stage in advance, and the method comprises the following steps: the server sets global model initialization parameters and broadcasts the global model initialization parameters to the client; the client calculates updated local parameters and constructs bit secret shares which are sent to the server; the server converts the bit secret shares into arithmetic secret shares, calculates 2 norms by using square sum tuples, checks the square sum tuples, aggregates parameters after the checking, updates a global model, and broadcasts the global model; and the application improves verification efficiency, reduces communication and calculation amount by constructing square sum tuples, and realizes safe exit of the client in multiple stages by designing a flow mechanism of dynamic exit of the client and task handover of the server, so that the flow and equipment robustness of parameter aggregation are enhanced without affecting operation of the protocol.