H04L2209/046

SECURE GRADIENT DESCENT COMPUTATION METHOD, SECURE DEEP LEARNING METHOD, SECURE GRADIENT DESCENT COMPUTATION SYSTEM, SECURE DEEP LEARNING SYSTEM, SECURE COMPUTATION APPARATUS, AND PROGRAM

A calculation of a gradient descent method in secure computing is performed at high speed while maintaining accuracy. A secure gradient descent computation method calculates a gradient descent method while keeping a gradient and a parameter concealed. An initialization unit initializes concealed values [M], [V] of matrices M, V (S11). A gradient calculation unit determines concealed value [G] of a matrix G of a gradient g (S12). A parameter update unit calculates [M] β1 [M]+(1−β1) [G] (S13-1), calculates [V]←β2 [V]+(1−β2) [G]◯[G] (S13-2), calculates [M{circumflex over ( )}]←β{circumflex over ( )}1, t [M] (S13-3), calculates [V{circumflex over ( )}]←β{circumflex over ( )}2, t [V] (S13-4), calculates [G{circumflex over ( )}]←Adam ([V{circumflex over ( )}]) (S13-5), calculates [G{circumflex over ( )}]←[G{circumflex over ( )}]◯[M{circumflex over ( )}] (S13-6), and calculates [W]←[W]−[G{circumflex over ( )}] (S13-7).

Multiplicative masking for cryptographic operations

A value corresponding to an input for a cryptographic operation may be received. The value may be masked by multiplying the value with a first number modulo a prime number. The cryptographic operation may subsequently be performed on the masked value.

MASKED DECODING OF POLYNOMIALS

Various embodiments relate to a method for masked decoding of a polynomial a using an arithmetic sharing a to perform a cryptographic operation in a data processing system using a modulus q, the method for use in a processor of the data processing system, including: subtracting an offset δ from each coefficient of the polynomial a; applying an arithmetic to Boolean (A2B) function on the arithmetic shares of each coefficient a.sub.i of the polynomial a to produce Boolean shares â.sub.i that encode the same secret value a.sub.i; and performing in parallel for all coefficients a shared binary search to determine which of coefficients a.sub.i are greater than a threshold t to produce a Boolean sharing value {circumflex over (b)} of the bitstring b where each bit of b decodes a coefficient of the polynomial a.

Fault detection

The present disclosure relates to a method of fault detection in an application, by an electronic circuit, of a first function to a message, including the steps of generating, from the message, a non-zero even number N of different first sets, each including P shares; applying, to the P shares of each first set, one or a plurality of second functions delivering, for each first set, a second set including Q images; and cumulating all the images, starting with at most Q-1 images selected from among the Q images of a same second set.

Converting a boolean masked value to an arithmetically masked value for cryptographic operations

A first input share value, a second input share value, and a third input share value may be received. The first input share value may be converted to a summation or subtraction between an input value and a combination of the second input share value and the third input share value. A random number value may be generated and combined with the second input share value and the third input share value to generate a combined value. Furthermore, a first output share value may be generated based on a combination of the converted first input share value, the combined value, and additional random number values.

Distributing a computation output

According to an aspect, there is provided a method of operating a first computing node to distribute a computation output, the method comprising: determining a first random mask; providing the first random mask as a private input to a computation by a first evaluator node and a second evaluator node; receiving, from each of the first evaluator node and the second evaluator node, a respective masked computation output, wherein each masked computation output is a function of an output of the computation and the first random mask; if the received respective masked computation outputs match, determining the output of the computation from the received masked computation output and the first random mask; and sending information to the first evaluator node and the second evaluator node to enable the first evaluator node and the second evaluator node to determine the output of the computation from the respective masked computation output.

Mobile device roaming optimization and operation

A method, system, and computer program product for implementing mobile device roaming optimization is provided. The method includes receiving a selection for services associated with a first mobile device provider for activation during travel to a location associated with mobile device roaming attributes with respect to a mobile device of a user. A blockchain structure and a hash masking sensitive data of the user are generated. It is detected that the user and mobile device have traveled to the location and access to the blockchain structure is enabled. Roaming usage attributes of the mobile device are determined. Subsequently, operational functionality of the mobile device at the geographical location is enabled via roaming usage of a network of the second mobile device provider and second hash of consumption related information compliant with data residency is transmitted to the first mobile device provider to facilitate resolution of disputes across entities.

Method to request sensitive data from a recipient and to establish a secure communication with the recipient
20230208619 · 2023-06-29 ·

The present system and method allow the exchange of messages, such as email, between a sender and a recipient while maintaining the data secure and the integrity of the content of the messages. The method and system do not require a user having an account to open a received message. The method comprises the server creating a new communication key upon reception of a request. The communication key is typically valid for a single request to ensure that each request is encrypted using different communication keys. The method typically comprises a client [A] establishing communication on [HANDSHAKE] with one or more servers [B]. The HANDSHAKE generally aims at initializing the encryption key that will be used to exchange information between A and B.

KEY EXCHANGE METHOD, KEY EXCHANGE SYSTEM, KEY DEVICE, TERMINAL DEVICE, AND PROGRAM

A random number generating unit generates random numbers s.sub.1, s.sub.2, s′.sub.1, and s′.sub.2. A public keys randomizing unit generates first randomized public keys information obtained by randomizing public keys using the random number s.sub.1 and second randomized public keys information obtained by randomizing the public keys using the random number s.sub.2. A proxy calculation unit calculates a first commission result by using a secret key and calculates a second commission result by using the secret key. A verification unit calculates a first verification value by using the random number s.sub.2, calculates a second verification value by using the random number s.sub.1, and verifies whether or not the first verification value and the second verification value coincide with each other. A common key calculation unit calculates a common key by using the random numbers s′.sub.1 and s′.sub.2 if the first verification value and the second verification value coincide with each other.

Privacy-preserving learning of web traffic

A method by one or more network devices communicatively coupled to a web application layer proxy for profiling parameters of web application layer requests received by the web application layer proxy while preserving privacy. The method includes obtaining masked parameter values associated with a parameter in the web application layer requests, where the masked parameter values associated with the parameter are generated by the web application layer proxy based on masking parameter values associated with the parameter while preserving lengths of the parameter values associated with the parameter and character types of characters in the parameter values associated with the parameter, generating the profile of the parameter based on analyzing the masked parameter values associated with the parameter, and providing the profile of the parameter to the web application layer proxy.