FULLY HOMOMORPHIC CRYPTOGRAPHY WITH IMPROVED DATA ITEM REPRESENTATION

    公开(公告)号:US20230396409A1

    公开(公告)日:2023-12-07

    申请号:US18250809

    申请日:2021-10-28

    申请人: ZAMA SAS

    发明人: Marc JOYE

    IPC分类号: H04L9/00 G06N3/048

    CPC分类号: H04L9/008 G06N3/048

    摘要: Some embodiments are directed to a fully homomorphic encryption (FHE) cryptography, wherein some encrypted data items are clipped, thereby reducing a bit-size of the encrypted data item and increasing an associated noise level of the encrypted data item. An FHE operation or a decrypt operation that operates on the clipped encrypted data item as input, has noise tolerance above a noise level associated with the clipped encrypted data item.

    SECURE PROVISION OF KEYS FOR FULLY HOMOMORPHIC ENCRYPTION

    公开(公告)号:US20230379136A1

    公开(公告)日:2023-11-23

    申请号:US18314534

    申请日:2023-05-09

    IPC分类号: H04L9/00 G06F9/4401

    CPC分类号: H04L9/008 G06F9/4401

    摘要: The present disclosure relates to a method including: the generation, by a computing device, of a first key and a bootstrapping key; the provision of the first key and an identifier of the bootstrapping key to an electronic device and the provision of the bootstrapping key and the identifier to a server; the fully homomorphic encryption, by the electronic device, of a first data value, stored in the electronic device, by using the first key; and the provision, by the electronic device, of the encrypted first data value and of the identifier, to the server.

    PRIVATE DECISION TREE EVALUATION USING AN ARITHMETIC CIRCUIT

    公开(公告)号:US20230379135A1

    公开(公告)日:2023-11-23

    申请号:US18221665

    申请日:2023-07-13

    申请人: SAP SE

    摘要: A non-interactive protocol is provided for evaluating machine learning models such as decision trees. A client can delegate the evaluation of a machine learning model such as a decision tree to a server by sending an encrypted input and receiving only the encryption of the result. The inputs can be encoded as vector of integers using their binary representation. The server can then evaluate the machine learning model using a homomorphic arithmetic circuit. The homomorphic arithmetic circuit provides an implementation that requires fewer multiplication than a Boolean comparison circuit. Efficient data representations are then combined with different algorithmic optimizations to keep the computational overhead and the communication cost low. Related apparatus, systems, techniques and articles are also described.

    Secure matching and identification of patterns

    公开(公告)号:US11816142B2

    公开(公告)日:2023-11-14

    申请号:US18105969

    申请日:2023-02-06

    IPC分类号: G06F16/51 H04L9/00 H04L9/08

    摘要: A framework is provided in which a querying agency can request (via a query entity) encrypted data through a service provider from a data owning agency that stores encrypted data. The framework uses homomorphic encryption. The data may be gallery entities, and each of the elements in the framework operate on doubly-encrypted information. The service provider compares a representation of an encrypted query entity from the querying agency and representations of encrypted gallery entities from the data owning agency, resulting in doubly-encrypted values of a metric between corresponding compared representations. The querying agency gets result(s), based on the metric, which indicate whether it is probable the service provider has data similar to or the same as query data in the query entity. The elements have to perform communication in order for the querying agency or the data owning agency to get cleartext information corresponding to the query entity.