42 results about "Oblivious transfer" patented technology

Example computer-implemented methods and systems for secure random noise generation are disclosed. One example method includes generating, by a first party, n random first bits and n -bit strings. The first party generates, based on the n -bit strings and the n random first bits, n pairs of -bit input messages. The first party performs n 1-out-of-2 oblivious transfers (OTs) of the n pairs of -bit input messages from the first party to a second party. The first party generates, based on the n -bit strings, a first random number. The first party performs, based on the first random number, secure multiparty computation (MPC) that involves the first party and the second party.

The embodiment of the invention provides a batch retrieval method based on a verifiable bloom filter and electronic equipment, and relates to the technical field of data security. The method comprises the following steps: converting a server data set into a key value pair form, and mapping keywords in the data set in the key value pair form into equal repeated codes through an equal repeated code mapping algorithm to obtain an equal repeated code data set; determining a storage position of a second verifiable bloom filter according to a keyword in the equal-repetition-code data set, and storing a data entry corresponding to the keyword in the equal-repetition-code data set and a check code generated based on the data entry to the storage position; the client receives the query keyword set and maps the query keyword set to the first verifiable Bloom filter; and taking each bit of the first verifiable Bloom filter as a selection vector to execute an oblivious transmission protocol to obtain a return result of the server side. The embodiment provided by the invention provides a safe and efficient batch retrieval method based on the verifiable Bloom filter.

The present disclosure provides a data processing method, apparatus, device, and storage medium, which can be applied to the fields of big data technology and encryption technology. The data processing method applied to the data demand side includes: processing preset screening threshold information through additive secret sharing to generate a first threshold secret shard and a second threshold secret shard; generating a first feature data set according to the first threshold secret shard and a first feature secret shard; generating a binary expansion set of the first feature data set; and obtaining a first screening mask data set from the data provider according to the binary expansion set by executing an oblivious transfer protocol; receiving a second encrypted data set and a third encrypted data set from the data provider; and obtaining a target data set by using a private intersection algorithm according to the first screening mask data set, the second encrypted data set, and the third encrypted data set.

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 disclosure provides a data matching method, and the method includes inputting to-be-matched first data into a pre-trained vector transformation model, to obtain a first vector corresponding to the first data and a binary vector corresponding to the first vector; obtaining a first intermediate vector using an oblivious transfer protocol, and obtaining a first distance intermediate result based on the first intermediate vector and a first predefined algorithm; receiving a second distance intermediate result generated, based on a second vector, a first random vector, and a second predefined algorithm, and sent by a second device; determining a target distance between the first vector and the second vector based on the first vector, the first distance intermediate result, and the second distance intermediate result; and determining whether the first data and second data match based on the target distance and a predefined first distance threshold.

Conducting secure transfers between computing devices can pose a challenge. Therefore, an oblivious transfer can be used to conduct a secure transfer. The oblivious transfer (OT) is an interactive protocol between two parties: a sender computing device and a receiver computing device. An OT protocol involves the sender computing device holding two messages m0 and m1, and the receiver computing device holding a bit b? {0, 1}. At the end of the protocol, the receiver computing device should only learn the message mb and nothing about the other message m1?b, while the sender computing device should learn nothing about the bit b. With the steady progress in quantum computing, several post-quantum oblivious transfer protocols can be derived.

The invention discloses a multi-party real-time auditing method and system for privacy calculation based on a block chain, and relates to the technical field of block chains, and the method comprises the steps: obtaining encrypted data, and transmitting the encrypted data to a calculation task based on a verifiable casual transmission mode, according to encryption of the encrypted data, the data provider encrypts the data and then carries out uplink evidence storage, a task initiator describes a calculation task by using a verifiable confusion circuit represented by Three-Halves and provides the calculation task to each data provider for calculation, and the circuit supports splitting. And zero-knowledge proof about the calculation task and encrypted data transmission is generated based on the encrypted data and the calculation task, and the auditing party verifies all the zero-knowledge proof about the calculation task and encrypted data transmission on the upload chain and publicizes an auditing result.

The present disclosure provides a data processing method, apparatus, device, and medium, which can be applied to the fields of big data technology and encryption technology. The data processing method applied to the data demand side includes: processing preset screening threshold information through the additive secret sharing method to generate a first threshold secret shard and a second threshold secret shard; generating a first feature data set according to the first threshold secret shard and the first feature secret shard; obtaining a third feature data set through the multiplicative secret resharing method according to the first feature data set and the second feature data set processed by the data provider using a preset parameter group; and obtaining a first screening mask data set from the data provider according to the third feature data set by executing the oblivious transfer protocol; receiving a second encrypted data set and a third encrypted data set from the data provider; and obtaining a target data set by using the private intersection algorithm according to the first screening mask data set, the second encrypted data set, and the third encrypted data set.

Example computer-implemented methods and systems for secure random noise generation are disclosed. One example method includes generating, by a first party, n random first bits and n l-bit strings. The first party generates, based on the n l-bit strings and the n random first bits, n pairs of l-bit input messages. The first party performs n 1-out-of-2 oblivious transfers (OTs) of the n pairs of l-bit input messages from the first party to a second party. The first party generates, based on the n l-bit strings, a first random number. The first party performs, based on the first random number, secure multiparty computation (MPC) that involves the first party and the second party.

The embodiments of this specification provide an oblivious transfer method and apparatus. Executed by a first party, wherein the first party maintains a global queue for storing obliviously transferred OT tuples, and multiple local queues maintained by taking OT tuples from the global queue; the method includes: for a first computing task, the first process of the first party obtains the first queue index of the first local queue allocated to the first computing task in the multiple local queues; when the first local queue is not empty, sequentially taking out OT tuples from the first local queue, and sending the first queue index to the second party, so that the second party sequentially takes out OT tuples from the local queue corresponding to the first queue index maintained locally, and performs oblivious transfer-based calculations with the second party using the OT tuples taken out by each party. It can meet the requirements of parallel processing, thereby improving operating efficiency.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating differential privacy noise. One example method includes generating, by a first party of two or more parties participating in a secure multiparty computation (MPC) instance, a first l-bit random number, where l is a positive integer; comparing a XOR result of the first l-bit random number and a second l-bit random number with an integer determined based on a target probability of a Bernoulli distribution, where the comparing comprises performing a comparison protocol based on oblivious transfer; and determining a Bernoulli sampling of a random number based on a result of the comparing. The Bernoulli sampling of the random number can be used to generate a random noise value, which can be added to an MPC computation result according to a differential privacy mechanism.

Example computer-implemented methods and systems for secure random noise generation are disclosed. One example method includes generating, by a first party, n random first bits and n -bit first strings. The first party generates, based on the n -bit first strings and the n random first bits, n pairs of -bit input messages. The first party receives n pairs of -bit second strings. The first party performs n 1-out-of-2 random oblivious transfers (ROTs) of the n pairs of -bit input messages from the first party to a second party. The first party generates, based on the n -bit first strings, a first random number. The first party performs, based on the first random number, secure multiparty computation (MPC) that involves the first party and the second party.

The disclosure provides a data matching method, and the method includes inputting to-be-matched first data into a pre-trained vector transformation model, to obtain a first vector corresponding to the first data and a binary vector corresponding to the first vector; obtaining a first intermediate vector using an oblivious transfer protocol, and obtaining a first distance intermediate result based on the first intermediate vector and a first predefined algorithm; receiving a second distance intermediate result generated, based on a second vector, a first random vector, and a second predefined algorithm, and sent by a second device; determining a target distance between the first vector and the second vector based on the first vector, the first distance intermediate result, and the second distance intermediate result; and determining whether the first data and second data match based on the target distance and a predefined first distance threshold.

The present invention is a privacy-preserving non-invasive load monitoring method for smart grids, which decomposes smart meter readings from the household level to the appliance level. This method enables a user and server to jointly perform a non-invasive load monitoring task based on a deep neural network under privacy-preserving conditions. The server utilizes a pre-trained model to provide prediction services, and the user maintains their own household-level smart meter readings. The present invention utilizes lattice-based homomorphic encryption, secret sharing, and an oblivious transfer protocol to apply privacy-preserving techniques to the deep neural network (PSPNet). This enables the privacy-preserving PSPNet deep neural network to be used for NILM tasks, addressing the security requirements of both users and servers in NILM tasks.

The application discloses a privacy protection set intersection method, system and device. The method comprises the following steps: sending first matrix data to a computing node of a data receiver and sending array data to a computing node of a data sender, wherein the first matrix data is generated based on a preset rule, and the array data is generated based on set elements of the data sender; the computing node of the data receiver and the computing node of the data sender generate second matrix data based on batch oblivious transfer; an index array is generated when a hash function value of the first matrix is equal to a hash function value of the second matrix, wherein the index array is determined based on an index value when the hash function value of the first matrix is equal to the hash function value of the second matrix; and the data sender data node and the data receiver data node obtain intersection elements based on the index array. Through the method, data security can be protected during set intersection.

This document describes systems and techniques for using cryptography, secret sharing, secure MPC, garbled circuits, and oblivious transfer to select digital components in ways that preserve user privacy and protects the security of data of each party that is involved in the selection process. A method includes obtaining, by a first computer of a secure multi-party computation (MPC) system, at least a first share of user data related to a user of a client device. For each digital component in a set, a first secret share of a condition bit for the condition is obtained for each of one or more conditions that condition eligibility of the digital component for distribution. A garbled circuit is executed to select a given digital component for which each of the one or more conditions of the digital component is satisfied using the first secret share and the second secret share for each condition.

The present invention relates to an oblivious transfer method for accessing commodity information based on blockchain. The method involves two objects: merchants and customers, and the method includes the following steps: S1: The merchant uploads the index information to the blockchain; S2: The customer retrieves the keyword and obtains the merchant address information; S3: The customer applies to the merchant to view the commodity information, the merchant sends the commodity information to the customer, and the customer selects one of them. This method constructs an n-out-of-one oblivious transfer based on the DH-based two-out-of-one oblivious transfer. Therefore, in terms of security, it inherits the security of the two-out-of-one oblivious transfer, that is, in each round, the merchant does not know whether the customer has selected the former or the latter. Among n data, the merchant cannot know which one the customer has selected, achieving privacy protection for browsing commodity information.

Methods for performing oblivious transfer are disclosed. These methods include a method for performing random single bit oblivious transfer (a “first method”), a method for performing random string oblivious transfer (a “second method”), and a method for performing non-random string oblivious transfer (a “third method”). In the first method, a sender computer can use a hardcore predicate function to obfuscate either a first message or a second message, generating an obfuscated message. The receiver computer can de-obfuscate this obfuscated message to randomly receive either the first message or the second message. The second method and third method can be implemented, with some modification, by repeatedly performing the first method, once for each “message bit” of the sender's messages. In the second and third methods, the receiver computer can send “indicator bits” to the sender computer, enabling the sender computer to transmit a random or non-random message strings to the receiver.

The present disclosure provides a method for laconic encryption, comprising: generating a public key and a secret key; computing a digest based on the public key; generating a ciphertext by combining the digest with a message; and decrypting the ciphertext using the secret key and non-secret decryption material. The method enables cryptographic primitives with sublinear communication complexity in two messages, where communication and computation complexity are essentially independent of the size of an input. The laconic encryption scheme is secure under the Learning With Errors assumption with polynomial modulus-to-noise ratio. The method can be used to construct laconic oblivious transfer, registration-based encryption, and laconic private-set intersection protocols with optimal parameters and practical efficiency. Additionally, the laconic encryption can be preprocessed for more efficient online encryption.

The invention discloses a construction method of an inadvertent pseudo-random function based on identity and an end-to-same-end encryption method realized by a national secret standard, and belongs to the technical field of data security. Blind cloud storage, portability, application server login embedded in a cloud storage server and deployable cloud storage data encryption are realized and met through an algorithm specified by a national secret standard. According to the method, the identity-based casual pseudo-random function is constructed by combining an identity-based pseudo-random function, a confusion circuit and a casual transmission protocol, a national secret standard implementation mode of the method of the identity-based casual pseudo-random function is given, and the identity-based casual pseudo-random function is realized by utilizing the national secret standard provided by the invention. And national secret standard implementation of the end-to-same-end encryption method is given.

Systems and methods for conducting composable quantum oblivious transfer over noisy quantum channels are disclosed. Embodiments provide a method for constructing a quantum oblivious transfer (QOT) protocol using noisy quantum channels and devices through the use of a quantum-hard one-way function. This construction allows the construction of QOT protocols that achieve simulator security, allowing them to be used in a black-box fashion as part of other cryptographic constructions, including arbitrary secure multiparty computations.

Embodiments can perform efficient OT (oblivious transfer) protocols to efficiently establish OT correlations that could be used for an MPC protocol. The present embodiments relate to a non-interactive OT (NIOT) protocol using a key encapsulation mechanism (KEM). Two OT protocols are non-interactive OTs, in which a sender generates private, public key pair (pk, sk) that is independent of its input or generated OT correlations. The two OT protocols use a cryptographic hash function and a one-way secure dense key encapsulation mechanism (KEM).

Disclosed are various embodiments for a mutual privacy-preserving transfer of information using natural language and oblivious transfer (OT) protocols. A receiver entity can send a response request with prompts and corresponding keys to a sender entity. The sender entity can generate the responses using an output of large language models. Before sending the responses to the receiver entity, the sender entity encrypts the responses. The receiver entity can only decrypt the response that is encrypted using the public key associated with the receiver entity.

The invention discloses a lattice threshold encryption Internet of Things data privacy protection method based on a zero-trust architecture. The method comprises the following steps: step 1, identity registration; step 2, performing threshold encryption based on a lattice; step 3, grid-based threshold key sharing is carried out; and step 4, a lattice-based sub-key volume transmission protocol. Based on zero trust and cryptography algorithms, the privacy of Internet of Things data in the circulation process is enhanced, and secure transmission of keys and sub-keys is realized by using threshold secret sharing and a crowd transmission protocol. An error-based lattice cryptographic algorithm is adopted to process the data of the Internet of Things, and privacy leakage of the data of the Internet of Things is prevented. And meanwhile, verification of equipment and a user in an Internet of Things system is realized by utilizing a zero-trust architecture, so that the security during data sharing is improved.

The application discloses an authentic high-efficiency n-taken-k careless transmission method and system, and the method comprises the following steps: S1, a system establishment step, wherein a trusted authority KGC outputs system public parameters mpk and a secret master private key msk based on input security parameters; S2, a key generation step, wherein the trusted authority KGC outputs a public-private key pair corresponding to the identity of the sender and the receiver to the sender and the receiver based on the identity information of the accepted sender and receiver; S3, a careless transmission step, wherein the receiver encrypts k own keys and sends them to the sender; the sender converts the k keys and encrypts n information to generate n ciphertexts, and then sends the k converted keys and the n ciphertexts to the receiver; and S4, a decryption step, wherein the receiver uses the k converted keys to decrypt the n ciphertexts to obtain k desired information. The identity authentication problem of the sender and the receiver in the careless transmission process is solved, and efficient encryption and decryption are realized.

Disclosed herein are system, method, and computer program product embodiments for evaluating a decision tree in a privacy preserving manner. In embodiments, s first server receives a first partial share of the decision tree and encrypted input data from a client, wherein the input data comprises a set of attributes. A second server receives a second partial share of the decision tree. Each of the first server and the second server communicate with the other server to compute a classification result over the encrypted input data using the respective partial share of the decision tree received thereby and secure multi-party computation methods, including additive homomorphic encryption and oblivious transfer, such that the classification result is computed without decrypting the encrypted input data, and such that the classification result is ultimately received by the first server. The first server then transmits the classification result to the client.

The present application relates to a kind of information anonymous tracking query method and system based on blockchain and inadvertent transmission extension, realize the data privacy transmission between query node and data node by inadvertent transmission extension, the privacy information retrieval system based on consortium blockchain, the keyword or customer ID information of the object to be queried of inquiring party hides the object to be queried, data service party provides matching query result but cannot know which specific query object corresponds to;Data does not go out and can calculate, eliminate the possibility of data caching, data leakage, data trafficking;The transmission mode on chain makes the calculation process of privacy information retrieval safe, traceable, supervisable, reaches the effect of security self-evidence;Compared with traditional privacy information retrieval based on OT, performance is higher.

Example computer-implemented methods and systems for secure random noise generation are disclosed. One example method includes generating, by a first party, n random first bits and n l-bit first strings. The first party generates, based on the n l-bit first strings and the n random first bits, n pairs of l-bit input messages. The first party receives n pairs of l-bit second strings. The first party performs n 1-out-of-2 random oblivious transfers (ROTs) of the n pairs of l-bit input messages from the first party to a second party. The first party generates, based on the n l-bit first strings, a first random number. The first party performs, based on the first random number, secure multiparty computation (MPC) that involves the first party and the second party.

The present invention discloses an encryption and decryption method, system and electronic device based on oblivious transfer extension. The method includes the following steps: Step 1: The sender and the receiver perform oblivious transfer; Step 2: The receiver sends the selected bit mask of the oblivious transfer to the sender; Step 3: The sender encrypts the original data and then sends it to the receiver; Step 4: The receiver decrypts the ciphertext sent by the sender. The present invention not only improves the efficiency of the protocol, but also expands the application scenarios of oblivious transfer, providing greater flexibility and operability for the deployment of actual systems.