A method includes obtaining, from a server, a filter including a set of encrypted identifiers each encrypted with a server key controlled by the server. The method includes obtaining a request that requests determination of whether a query identifier is a member of a set of identifiers corresponding to the set of encrypted identifiers. The method also includes transmitting an encryption request to the server that requests the server to encrypt the query identifier. The method includes receiving, from the server, an encrypted query identifier including the query identifier encrypted by the server key and determining, using the filter, whether the encrypted query identifier is not a member of the set of encrypted identifiers. When the encrypted query identifier is not a member of the set of encrypted identifiers, the method includes reporting that the query identifier is not a member of the set of identifiers.

Embodiments are disclosed for a method. The method includes validating training data that is provided for training a machine learning model using ordinary differential equations. The method further includes generating pre-processed training data from the validated training data by generating encrypted training data from the validated training data using homomorphic encryption and generating random noise based on the validated training data. The method also includes training the machine learning model adversarially with the pre-processed training data.

A storing information generation apparatus obtains registration information and an identifier capable of identifying the registration information, to generate a first individual key from the common key and the identifier, and to generate storing information obtained by linearly converting the registration information using the common key and the first individual key. A matching information concealment apparatus obtains matching information to generate concealed matching information concealing the matching information using an encryption key. A concealed similarity calculation apparatus calculates a concealed similarity from the storing information and the concealed matching information. A decryption apparatus generates a second individual key from the common key and the identifier, and calculates a similarity between the registration information and the matching information from the concealed similarity, a decryption key corresponding to the encryption key, the common key, and the second individual key.

Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

An arithmetic apparatus includes an interface and a circuity. The interface is connected to an information processing apparatus that is connected to a client apparatus and that processes data in an encrypted state. The circuitry acquires, from the information processing apparatus, encryption input data or encryption target data encrypted with a first encryption key. The circuitry decrypts the acquired, encryption input data or encryption target data with a first decryption key. Then, the circuitry executes a predetermined arithmetic operation on the decrypted arithmetic operation target data, encrypts data of an arithmetic operation result obtained by the predetermined arithmetic operation with the first encryption to key, and outputs the encrypted data of the arithmetic operation result to the information processing apparatus.

Disclosed is a system for executing a data access transaction. The system comprises a server arrangement, the server arrangement being communicably coupled with at least one requesting device and at least one responding device. The server arrangement is configured to receive from a requesting device and a responding device, a first data and a second data respectively, wherein the first data and the second data are encrypted and temporally defined. Further, the server arrangement receives from the requesting device a metadata of the first data, wherein the metadata is encrypted by the requesting device, determines an encrypted association score by comparing the first data and the second data, wherein the encrypted association score is based on a temporally defined dynamic evaluation component, wherein the temporally defined dynamic evaluation component includes a causality measure, wherein the causality measure is able to identify and exclude spurious correlations between the first data and the second data and provides the encrypted association score to the requesting device and the responding device, wherein each of the requesting device and the responding device partially decrypt the encrypted association score. Further, the server arrangement obtains the partial decryption of the encrypted association score from the responding device and provide the partial decryption to the requesting device, wherein the requesting device fully decrypts the encrypted association score using the partial decryption obtained from the responding device and enables the requesting device to access the second data from the responding device, upon receiving a request for the access to the second data.

Provided are a training method and apparatus for a distributed machine learning model, a device and a medium. The training method includes: acquiring a first homomorphic encryption intermediate parameter and a second homomorphic encryption intermediate parameter; generating a first interference parameter, and forming a first encryption interference parameter by encrypting the first interference parameter by using a second homomorphic public key of a second participant; performing calculation based on the first homomorphic encryption intermediate parameter, the second homomorphic encryption intermediate parameter, the first encryption interference parameter and the homomorphic calculation function of a first submodel to generate a first encryption key parameter.

A secure table reference system includes a first combining part 11.sub.n for generating [v′] of v′ ∈ F.sup.m+nt in which d and v are combined, a difference calculation part 12.sub.n for generating [r″] of r″ that has a difference between a certain element of r and an element before the certain element as an element corresponding to the certain element, a second combining part 13.sub.n for generating [r′] of r′ ∈ F.sup.m+nt in which r″ and an m-dimensional zero are combined, a permutation calculation part 14.sub.n for generating {{σ}} of a permutation σ that stably sorts v′ in ascending order, a permutation application part 15.sub.n for generating [s] of s: =σ(r′) obtained by applying the permutation σ to r′, a vector generation part 16.sub.n for generating [s′] of a prefix-sum s′ of s, an inverse permutation application part for generating [s″] of s″ obtained by applying an inverse permutation σ.sup.−1 of the permutation σ to s′, and an output part 17.sub.n for generating [x] of x ∈ F.sup.m consisting of (n.sub.t+1)th and subsequent elements of s″.

One embodiment provides a processor comprising first circuitry to decode an instruction into a decoded instruction, the instruction to indicate a first source operand and a second source operand and second circuitry including a processing resource to execute the decoded instruction, wherein responsive to the decoded instruction, the processing resource is to output a result of first source operand data minus second source operand data in response to a determination by the processing resource that the first source operand data is greater than or equal to the second source operand data, otherwise the processing resource is to output the first source operand data.

A homomorphic encryption device includes: a recryption parameter generating circuit, a recryption circuit, and an arithmetic circuit. The recryption parameter generating circuit is configured to generate a recryption parameter including a plurality of recryption levels respectively for a plurality of ciphertexts based on an arithmetic scenario including information about an arithmetic schedule between the plurality of ciphertexts. The recryption circuit is configured to generate a plurality of recrypted ciphertexts by recrypting each of the plurality of ciphertexts to a corresponding recryption level based on the recryption parameter. The arithmetic circuit is configured to output an arithmetic result by performing operations by using the plurality of recrypted ciphertexts, according to the arithmetic scenario.