36 results about "Trust third party" patented technology

The invention discloses a privacy protection federated learning method based on result-agnostic function encryption, and the method comprises the steps: dividing a derived key assembly into a plurality of shares, and carrying out the reconstruction through the remaining shares even if a part of clients are offline and the key shares are missing, thereby guaranteeing that a function key can be recovered, and an encryption model can be correctly aggregated, and improving the privacy protection efficiency. And the robustness and fault tolerance of the system are greatly improved. A non-interactive key exchange technology is adopted, and a secret sharing mechanism is combined, so that a client can generate a private key in a collaborative manner under the condition that no trusted third party participates, the deployment complexity is reduced, and the security and expandability of the system are improved. A function encryption process with an unknown result is designed, only an intermediate result in an encrypted state is output in an aggregation stage, and decryption is finally completed by local joint of a client, so that the possibility of snooping an aggregation result and reversely deducing original data by a server under a semi-honesty model is fundamentally avoided, and data privacy in a federated learning process can be effectively guaranteed.

The application provides a third-party-based key exchange method and system, a trusted third party and an entity, wherein the trusted third party only participates in identity authentication of the entity and assists in negotiation of a key between the two entities, and cannot obtain a shared key between the two entities, effectively solving the problem that the trusted third party cannot avoid obtaining the exchanged key in the existing key exchange scheme based on the trusted third party, and ensuring that the finally exchanged key is only owned by the two entities participating in the key exchange. In addition, in the application, the trusted third party can also provide a random number to participate in the final key generation, thereby ensuring the strength of the final key, meeting the requirement that the trusted third party needs to manage the strength of the exchanged key in a specific application scenario, and enhancing the management and control capability of the system.

We provide computing systems and methods for communicating with customer devices and trusted third parties. [Solution] In the currency conversion system, the network interface receives customer identity data and a request to restore the customer wallet from the customer device. The processor verifies the customer identity data received from the customer device. Once the processor has verified the customer identity data received from the customer device, the network interface communicates a request to a trusted third-party key repository for a first key associated with the customer wallet. The processor uses the first key associated with the customer wallet and a second key associated with the customer wallet to restore the customer wallet.

The application belongs to the technical field of encryption, and provides an anti-quantum threshold encryption method and system, wherein a trusted third party generates system parameters, uniformly and randomly generates a matrix, samples a secret vector and a noise vector, calculates a public key vector, and discloses the matrix and the public key vector as a public key; a unique and public identification value is allocated to each authorized accesser, a private key share is calculated, and the private key share is sent to the authorized accesser respectively; a data owner acquires a message to be encrypted and the public key, calculates a ciphertext, and the ciphertext comprises a first component and a second component; an authorized accesser participating in decryption reads the first component of the ciphertext, calculates a partial decryption value, and sends the identification value and the partial decryption value to the trusted third party; when the trusted third party receives the partial decryption values of no less than a threshold parameter, Lagrange coefficients are calculated, an aggregated decryption value is calculated, the decryption of the ciphertext is carried out, and the obtained result is sent to the authorized accesser participating in decryption. The application can guarantee the confidentiality of the message.

The invention relates to the technical field of data security, in particular to a bank asset electronic auction algorithm based on homomorphic encryption, which comprises key generation and distribution, hybrid encryption quotation, threshold decryption and verification and result publication. Compared with the prior art which depends on a non-completely trusted third party to realize the auction process, the scheme adopts a decentralized (t, n) threshold decryption mechanism, combines a Shamir secret sharing technology, splits a private key into multiple parts and distributes the multiple parts to all participants, and decryption needs at least t nodes to cooperate to complete. In the prior art, a centralization risk is caused by dependence on a single third party, and control by an attacker or single-point failure is easily caused; according to the scheme, through distributed key management and threshold verification, third-party dependence is eliminated, it is ensured that even if part of nodes are malicious or invalid, the result can still be safely decrypted and verified, and the collusion attack resistance and fault tolerance of the system are remarkably improved.

The application discloses a mass interface call log storage and tracing method and system based on a blockchain, belongs to the technical field of the blockchain, and aims to solve the problems of mass interface call log storage difficulty and data sharing tracing difficulty in a data sharing mode. A service gateway pushes a call log to a Kafka cluster; the Kafka cluster consumes the call log and stores the consumed call log in batches to an ES system through logstash; a log collection system uploads a total hash value corresponding to the batch call log to the blockchain, the blockchain returns a transaction hash value to the log collection system, the log collection system returns the transaction hash value to the ES system and associates the transaction hash value with the corresponding batch call log; a trusted third party calculates a total hash value of the corresponding batch call log, compares the obtained total hash value with the total hash value queried from the blockchain, and determines that the call log is trusted if the total hash values are consistent.

The disclosed technology provides for managing, authenticating, and authorizing data sharing between parties utilizing multi-party-computation ("MPC"). A method can include: receiving, by a server from a party B system, (i) a request to access first data of a party A system and (ii) second data of party B, sending, to the party systems, an authorization request to authorize the request, receiving, from the party systems, MPC shares associated with trusted third party processing of data, the MPC shares generated as part of a digital contract between the parties for combining the first and second data within an environment of the trusted third party, to which neither party has access, retrieving MPC authorization functions associated with the digital contract, determining whether the requested access is authorized based on the MPC shares and MPC authorization functions, and performing data processing operations using the first and second data in a secure environment.

Embodiments of the present disclosure provide a multimedia data stream processing method and apparatus, an electronic device and a storage medium. The method comprises: receiving stream pushing related data sent by a stream pushing node, wherein the stream pushing related data corresponds to a pushed multimedia data stream; determining a target processing policy on the basis of the stream pushing related data and reception related data of a received processed multimedia data stream forwarded by a trusted third party; and when the target processing policy is a stream repushing policy, creating a data transmission link corresponding to the trusted third party and a current receiver so as to push, on the basis of the created data transmission link, the multimedia data stream pushed by the stream pushing node to the trusted third party. The technical solution provided by the embodiments of the present disclosure can ensure that the trusted third party forwards the multimedia data stream to the current receiver, achieving the effect of improving the forwarding service quality and stability.

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.

A method, system, device and medium for defending against poisoning attacks in vertical federated learning, an active party and passive party interaction data integrity verification scheme is designed for the classic vertical federated learning algorithm Secureboost, the method is: key generation and distribution; the active party encrypts the Boost tree gradient information, and sends the encrypted result to the passive party, and sends the encrypted Boost tree gradient information to the trusted third party after homomorphic hash encryption; the passive party aggregates the received encrypted gradient information according to the feature dimension, and then performs homomorphic hash on the aggregation result and sends it to the trusted third party; the trusted third party aggregates all the information sent by the passive party, and then verifies whether the encrypted Boost tree gradient information sent by the active party and the aggregation result of the passive party information are consistent, if consistent, the integrity verification is passed, otherwise the verification is failed; the system, device and medium based on the above method defend against poisoning attacks, realize the safe aggregation of global model, and improve the defense reliability of poisoning attacks.

The application discloses a kind of fusion attack traceability and data integrity audit federated learning method and system, the method includes: trusted third party initializes system parameter, system parameter and initial model parameter are sent to all clients;Gradient and four characteristics returned by each client are received, attack traceability and reputation evaluation are carried out to four characteristics, determine the client set of next round continues training;Gradient set is sent to aggregation server after encryption, receive the encrypted aggregation gradient returned by aggregation server, obtain aggregation gradient plaintext by decryption;The present application is processed by client homomorphic encryption, attack detection and traceability, secure multi-party aggregation, encrypted reputation management, hierarchical process of independent integrity verification, malicious attack is identified and traced to next round training before model, so that attack detection is realized under the premise of guaranteeing privacy not to leak, reduce the overall security risk of federated learning system.

The application relates to the fields of secure multi-party communication and quantum cryptography, and discloses a dynamic quantum message authentication method capable of identifying suspension, which comprises the following steps: a semi-quantum trusted third party (SQ-TTP) screening honest participant phase, in which the SQ-TTP dynamically groups the participants, randomly selects part of the participants to form a small quantum communication network for message transmission, and screens out no less than the number of groups of honest participants according to the message authentication result; a parallel transmission of quantum messages of each group phase, in which the SQ-TTP specifies the screened honest participants as the receivers of each group, and the participants in the group complete the message transmission by adopting a quantum message transmission mode similar to that in the screening phase; and a stage of transmitting the received messages to a server by the SQ-TTP and the receivers of each group, in which the server decrypts the messages by using the key sent by the SQ-TTP, and authenticates the messages by measuring the trap qubits. The application is applicable to a large-scale quantum communication network, and can reduce the consumption of quantum resources and improve the message transmission efficiency by dynamic grouping and parallel transmission.

The present invention provides a secure aggregation method based on random exchange and key homomorphic pseudorandom functions, specifically comprising: in an initial stage, a user randomly selects n other users and exchanges the generated random numbers with them respectively; after the exchange, the total amount of the users' random numbers is calculated and sent to a control center; in a sending stage, a ciphertext is formed by a modular addition homomorphic operation based on the current time period, the user's electricity consumption, and the key obtained in the initial stage, and the ciphertext is summed up at the gateway and sent to the control center; in a decryption stage, the obtained ciphertext sum and the total amount of random numbers corresponding to the ciphertext sum are decrypted to obtain the total electricity consumption; in a management stage, new users are added, old customers are withdrawn, or the user's smart meter malfunctions are managed. The beneficial effects of the present invention are: no trusted third party is required, multiple solutions are adaptable, implementation is convenient, user management is lightweight, and while ensuring the security and accuracy of the results, additions and deletions can be freely made, resulting in strong applicability.

The invention relates to an anonymous data submission method based on a hash mask, and belongs to the technical field of data security. According to the method, all data senders generate session keys between every two data senders under the assistance of a data receiver, and then the senders randomly join one of m groups respectively; all data senders generate unique serial numbers which are different from one another under the condition that a trusted third party does not need to participate, and it is guaranteed that the values of the serial numbers can be deduced by no other entities except the data senders; all the data senders carry out packaging protection on own data by using own serial numbers and session key sequences; a data receiver obtains all the packaged data and unpacks the packaged data to obtain a set of original plaintext data, but cannot deduce the source of the data. According to the method and the device, the data receiver can obtain the data submitted by the data provider without a trusted third party, and the data receiver cannot deduce the source of the data, so that the identity anonymity of the data provider is guaranteed.

The application discloses a kind of distributed flow table item effective time dynamic hopping implementation methods, including distributed flow table item effective time dynamic hopping definition, implementation, and balance security, performance and resource consumption three features such as characteristic.This method, flow table item in flow table existence time is regarded as privacy, through the ladder random response mechanism of differential privacy in SDN forwarding equipment local flow table item in flow table existence time is dynamically disturbed, forms dynamic mobile flow table item attack surface, makes low-speed flow table overflow attack unable to synchronize flow table item attack surface, to the attack has realized effective active defense.The method does not need to upgrade existing SDN interface protocol and controller software, does not need to introduce trusted third party, while considering network security, guarantee network performance and expansibility, especially suitable for various types of need to support high security and large concurrent user, and has special requirements to delay and expansibility, guarantee its service quality and user experience.

The disclosed technology provides for managing, authenticating, and authorizing data sharing between parties utilizing multi-party-computation ("MPC"). A method can include: receiving, by a server from a party B system, (i) a request to access first data of a party A system and (ii) second data of party B, sending, to the party systems, an authorization request to authorize the request, receiving, from the party systems, MPC shares associated with trusted third party processing of data, the MPC shares generated as part of a digital contract between the parties for combining the first and second data within an environment of the trusted third party, to which neither party has access, retrieving MPC authorization functions associated with the digital contract, determining whether the requested access is authorized based on the MPC shares and MPC authorization functions, and performing data processing operations using the first and second data in a secure environment.

This invention discloses an efficient threshold multi-party computation method and system based on homomorphic encryption in a decentralized model. The method specifically includes the following steps: (1) each participant agrees on common parameters; (2) each participant generates its own private key; (3) each participant uses its private key multiplied by the parameters and adds noise to generate a public key; (4) each participant uses its public key to encrypt its own plaintext to obtain ciphertext; (5) each participant expands the ciphertext; (6) addition and tensor product function calculations are performed, and the calculated ciphertext is output; (7) the ciphertext from step (6) is relinearized; and (8) the ciphertext from step (7) is decrypted. This invention can solve the problems of trusted third parties, algorithm paralysis after participant corruption, and low efficiency in relinearization in existing multi-party computation based on homomorphic encryption in cloud computing.

The present invention relates to the field of network information security technology, and in particular to an access token application control method based on an attribute encryption mechanism, comprising the following steps: S1, a trusted third party generates public parameters of the attribute encryption mechanism: Setup(λ)→(params, mpk, msk), generates system parameters params, a master public key mpk, and a master private key msk; S2, the trusted third party generates a private key of a user attribute ω for a user: KeyGen(mpk, msk, ω); S3, a server performs attribute encryption on the access token: Encrypt(mpk, A, m): encrypts the access token m∈{0, 1}* in the set of authorized user attribute strings A; S4, the user receives the ciphertext access token and performs attribute decryption: Decrypt(ct, sk): decrypts the ciphertext access token ct using the user's private key sk. The present invention can encrypt the access token using the attribute encryption mechanism according to the user's access permission attributes, thereby ensuring that the access token cannot be correctly decrypted even if the attributes are changed due to a change in user permissions or a network attack.

The invention discloses a power consumer behavior anomaly detection method and system supporting privacy protection, and relates to the field of power data processing. The method comprises the following steps: a trusted third party generates and distributes an encryption key and a confusion matrix; preprocessing the power utilization data; data privacy protection is realized through linear transformation and encryption; the cooperative training model of the double-cloud server encrypts transmission gradient update parameters; and finally outputting an anomaly detection result. Through hierarchical encryption, feature optimization and cooperative training, high detection precision is maintained and communication overhead is reduced while privacy of user data and model parameters is guaranteed, so that the method is suitable for an abnormal power utilization monitoring scene of a smart power grid.

The present invention provides a method and system for detecting free-rider attacks in privacy-preserving vertical federated learning, relating to the field of data processing. The method comprises: generating a first ciphertext representation based on a local bottom model and receiving a second ciphertext representation sent by each passive participant; determining the maximum mean difference in ciphertexts corresponding to the passive participant based on the first and second ciphertext representations; sending the maximum mean difference in ciphertexts to a trusted third party, and receiving a free-rider detection result from the trusted third party. The free-rider detection result is determined by decrypting the maximum mean difference in ciphertexts by the trusted third party to obtain the maximum mean difference in plaintexts and applying a preset threshold. The preset threshold is determined based on multiple rounds of training. During training, the passive participant updates the bottom model based on update information sent by the active participant, with the update information being determined based on gradient information and the maximum mean difference in ciphertexts. The present invention can protect private data in vertical federated learning and detect free-rider attacks.

The present invention discloses a method for quantum homomorphic encryption ciphertext retrieval based on a trusted third party. First, a user requests a trusted third party to retrieve specific data from user data; the trusted third party prepares a corresponding plaintext superposition state based on the user's search request; then the trusted third party and a cloud server collaborate to homomorphically execute the quantum Grover algorithm on the plaintext superposition state based on the number of Grover iterations; the trusted third party measures the quantum state after the search, and the obtained measurement result is the solution corresponding to the search request; then the trusted third party shares a string of identical keys with the user through quantum key distribution technology, encrypts the measurement result using the shared key, and sends the encrypted measurement result to the user; the user then decrypts the encrypted measurement result using the shared key to obtain the solution corresponding to the proposed search request. This method can effectively improve the efficiency and security of ciphertext retrieval, and achieve fast and secure ciphertext retrieval.

The invention discloses a group chat message tamper-proofing method, which comprises the following steps of: constructing an intimacy degree matrix of group chat members, and dynamically calculating element values of the intimacy degree matrix based on message interaction frequency among the members; for a to-be-verified message sequence, performing confirmer group screening operation based on the matrix, including first screening based on a high intimacy degree and second screening based on a low intimacy degree; the confirmer group confirms the message sequence, generates a confirmation message with a digital signature and submits the confirmation message to the block chain; and based on the confirmation message stored in the block chain, carrying out tamper-proof verification on the content and sequence of the message sequence. According to the method, verification node selection is optimized by using the dynamically calculated intimacy degree matrix and a dual screening mechanism, efficient and reliable tamper-proof verification of the group chat message is realized on the premise of not needing a trusted third party, the verification efficiency is effectively improved, and collusion cheating is prevented.

The invention relates to the technical field of data security, in particular to a data access method based on a dynamic token, electronic equipment and a storage medium, the method comprises the following steps: in response to a token application request of a first entity, generating and issuing a data access token to the first entity through a preset trusted third party, the second entity triggers a verification request after receiving a data access request carrying the data access token sent by the first entity, the preset trusted third party receives the verification request for the data access token sent by the second entity, the validity of the data access token is verified through the preset trusted third party, and a verification result is returned to the second entity; the execution of the data access request of the first entity by the second entity is controlled; according to the invention, the current authority of both parties of the data transaction can be verified at the same time, so that the data transaction security during data interaction between cross-domain or mutual-mutual-trust entities is ensured.

In a trust framework that enables secure communication, a configurer establishes an initial set of potential trusted relationships between a client and one or more anchors associated with one or more hosts. Once configured, the client can use a trusted relationship to securely communicate with a host without reliance on trusted third parties.

Systems, apparatus, methods, and articles of manufacture for validating accuracy of artificial intelligence models are disclosed. An example apparatus includes machine readable instructions; and at least one processor circuit programmed by the machine-readable instructions to: compute accuracy statistics for an artificial intelligence model using software and an input data set applied by a trusted third party; determining the signed article based on: (1) accuracy statistics indicative of the accuracy of the artificial intelligence model, (2) software applied by the trusted third party, and (3) an input data set; and communicating the signed article to a user of the artificial intelligence model.

A concise non-interactive zero-knowledge proof generation method based on distributed calculation comprises the following steps: respectively carrying out (1) distributed zero test, (2) distributed replacement test, meta-distributed reset test and distributed fraction summation test, carrying out distributed summation test on the results of the two tests, and then carrying out distributed polynomial commitment. And security authentication is realized. According to the method, the generation speed of the certification in a simple non-interactive zero-knowledge certification protocol is remarkably improved through distributed calculation, meanwhile, a universal arithmetic circuit is supported (no special structure is needed), a trusted third party is not needed for execution in the initialization stage, currently known quantum algorithm attacks can be resisted, and the method is suitable for popularization and application. And only communication traffic of logarithmic polynomial magnitude is needed in the distributed system.

The invention belongs to the technical field of unmanned aerial vehicle Internet security, particularly relates to an unmanned aerial vehicle Internet identity authentication and key negotiation method, system and terminal, and designs an authentication and key negotiation method for an unmanned aerial vehicle dynamic group in order to solve the problem of secure communication between an unmanned aerial vehicle and each physical node in the unmanned aerial vehicle Internet. In the designed method, anonymity and privacy protection of UAV identity information are realized based on a symmetric encryption algorithm by introducing a trusted third-party mechanism; lightweight unmanned aerial vehicle identity authentication and group session key distribution are realized by using uniqueness and unclonability of the PUF, a message authentication code and secret sharing; when the UAV needs to join or exit the group, the join or exit of the UAV is realized based on a secret sharing scheme.

The invention belongs to the technical field of encryption, and provides an anti-quantum threshold encryption method and system, a trusted third party generates system parameters, uniformly and randomly generates a matrix, samples a secret vector and a noise vector, calculates a public key vector, and publishes the matrix and the public key vector as public keys; distributing a unique and public identification value to each authorized visitor, calculating a private key share of the authorized visitor, and sending the private key share to the authorized visitor; the data owner obtains a to-be-encrypted message and a public key and calculates a ciphertext, and the ciphertext comprises a first component and a second component; an authorized visitor participating in decryption reads the first component of the ciphertext, calculates a partial decryption value, and sends the identification value and the partial decryption value to the trusted third party; and when the trusted third party receives a partial decryption value not less than the threshold parameter, calculating a Lagrange coefficient, calculating an aggregation decryption value, decrypting the ciphertext, and sending an obtained result to an authorized visitor participating in decryption. According to the invention, the confidentiality of the message can be ensured.

The invention belongs to the cross field of distributed machine learning and information security technology, and relates to a federated learning participant optimization selection method and system of an integrated block chain, and a trusted third party under the block chain generates a homomorphic encryption key; the homomorphic encryption key comprises an encryption public key and an encryption private key; a participant obtains a historical global model and an encrypted public key based on the block chain, trains and encrypts a local model, and uploads the local model to the block chain; a network node generates a participant selection scheme through iteration, obtains an encryption aggregation model by combining homomorphic encryption, and sends the encryption aggregation model to a trusted third party through an intelligent contract; the trusted third party decrypts the encryption aggregation model based on the encryption private key and calculates a fitness value, and the smart contract screens an optimal participant selection scheme based on the fitness value; the smart contract generates a global model based on the optimal participant selection scheme and writes the global model into the block chain; and circularly executing the process until federal learning meets a preset target condition. According to the method, decentration is realized on the architecture level, and high-quality participants are efficiently screened out.

The application discloses a kind of efficient data sharing methods based on block chain, can solve the problems, such as data storage concentration, search algorithm inefficiency existing in current data sharing process, realize safe and efficient decentralized data sharing.The encrypted data is stored in interstellar file system (IPFS) to obtain content identifier (CID);Key words are hashed, form keyword index with CID, and are stored on blockchain.Finally, searchable encryption algorithm based on inverted index is used, and the query operation on related data is realized by generating search trapdoor.Data users initiate query request based on discrete logarithm problem, and data owners can realize authorization operation without the participation of trusted third party.The application can maintain good search efficiency when the number of indexes is large, and realize decentralized data sharing without the supervision of trusted third party, so that the data sharing of each organization is safer, more efficient and convenient.