Abstract:
A machine learning method including a first learning phase for training parameters θ of a learning model f by performing machine learning using a first dataset as a training data with a correct answer label; and a second learning phase for training parameters τ of a defender u and parameters ω of identifier h by performing machine learning using member data contained in the first dataset and non-member data contained in a second dataset. The second learning phase alternately performs, a first step for updating the parameters ω of the identifier h using the identification result when the first input result and the second input result are input to the identifier h; and a second step for updating the parameters τ of the defender u using the first output result, the second output result and the identification result.
Abstract:
An authentication system is provided with: a user device; user side assistance device(s) to assist user authentication that authenticates a user of the user device, and apparatus authentication that authenticates the user device; and an apparatus authentication server device to perform apparatus authentication in association with the user device. The user side assistance device(s) use distributed shares of verification information to perform multi-party computation for user authentication in association with the user device, and use distributed shares of a secret key generated by the user device, to perform multi-party computation for apparatus authentication in association with the user device.
Abstract:
An intermediate apparatus that upon reception of a request from an application apparatus, instructs a plurality of secure computation apparatuses to perform a secret computation processing, in accordance with the request, performs a part of operation of the request from the application apparatus, on at least one of a part of data included in the request or data reconstructed from shares received from a plurality of secure computation apparatuses.
Abstract:
A learning apparatus according to the present example embodiment includes: a data dividing unit that generates n sets of divided data by dividing first learning data into n (n is an integer of 2 or more); an inference device generation unit that generates n inference devices for learning data generation by machine learning using data excluding one set of divided data from the first learning data; a learning data generation unit that generates second learning data by inputting the one set of the divided data excluded from the machine learning into each of the n inference devices for learning data generation; and a learning unit that generates a second inference device by machine learning using the second learning data.
Abstract:
The invention includes a first learning phase that a machine learning is performed using first dataset to create a learning model f; and a second learning phase that the first or a second dataset is randomly selected; a result by inputting the first and the second datasets to the learning model f is inputted to a discriminator h having a parameter ω; a machine learning is performed using a result and a ground truth data to train the parameter ω, the result being obtained by having the discriminator h discriminate whether the input data belongs to the first or the second dataset; and when the first dataset is selected, a result by inputting the data of the first dataset to the learning model f is inputted to a defender u to train a parameter τ thereof by using an output of the discriminator h through the defender u.
Abstract:
A system includes a plurality of nodes, an individual one of which transmits data to which a group signature is attached, and a plurality of management servers that are directly connected to each other. An individual one of the plurality of management servers includes a ledger for managing data received from the nodes. Addition of data to the ledger of at least one of the plurality of management servers is reflected on the ledgers of the other management servers.
Abstract:
A registration apparatus generates shares by secret sharing of a character string with a plurality of modulus and sends the shares to a plurality of server apparatuses to be stored therein. A retrieval apparatus sends shares generated by secret sharing of a retrieval character string with the plurality of modulus to the plurality of server apparatuses. The plurality of server apparatuses execute a subroutine for shares of the each registration character string stored in a storage unit and for each of the plurality of modulus, reconstruct an execution result, and determine whether or not to return the shares of the registration character string stored in the storage unit as a retrieval result. A retrieval apparatus reconstructs shares returned from the plurality of server apparatuses and obtains a retrieval result in which the retrieval character string hits, from the reconstructed result by the Chinese remainder theorem.
Abstract:
Provided is a database search device that, when searching an external database, efficiently executes any search command even if the usable search commands are restricted. The database search device comprises: a search command separating unit that separates input search commands into a first search command that can be executed in a prescribed database and a second search command that cannot be executed in the prescribed database; and a search command execution unit that provides the search results obtained by executing the second search command on the search results obtained by executing the first search command in the prescribed database, as the search results for the input search command.