Panasonic Intellectual Property Corporation of America

Nuttapong Attrapadung

Yuji Unagami

Goichiro Hanaoka

Takahiro Matsuda

Naohisa Nishida

Shota Yamada

Tatsumi Oba

Tadanori Teruya

Natsume Matsuzaki

Ryo Kato

A secure authentication method includes: deriving a distributed LSH value using secret LSH, taking a first distributed feature amount which is a feature amount of user information distributed through a secret distribution method and encrypted LSH parameters as inputs; deriving a distributed hash value using a secret unidirectional function, taking the distributed LSH value and a distributed key as inputs; decoding the hash value by reversing distribution of the distributed hash value; selecting, from a secret hash table storing sets of a hash value as an index and a distributed feature amount as a data string, a set including a hash value matching the decoded hash value; computing, in secret, similarity between the distributed feature amount in the set and the first distributed feature amount; deriving, in secret, a user authentication result based on the similarity computed; and outputting the derived authentication result.

Secure authentication method and secure authentication system

A method of obtaining a shared prediction model is provided. The method includes: obtaining a prediction model as a neural network; converting each negative numerical value in a plurality of parameters included in the prediction model to a positive numerical value to obtain a converted prediction model; and sharing the converted prediction model by a secret sharing method to obtain shared prediction models while concealing an input data.

Prediction model sharing method and prediction model sharing system

In an information processing method, a query including a first encrypted feature value provided with confidential information unique to a user is received. The first encrypted feature value is generated by encrypting a first feature value calculated from privacy data of the user by using inner product encryption. A plurality of inner product values are acquired by computing an inner product of the first encrypted feature value and each of a plurality of second encrypted feature values. Privacy data of a plurality of pieces of privacy data having an inner product value of the first encrypted feature value and a second encrypted feature value with an encrypted reference feature value calculated from the privacy data being equal to or smaller than a predetermined threshold is transmitted. A secret key of the user is identified by using the confidential information when an unauthorized access is detected, and identification information is outputted.

Information processing method and information processing system

A data search method of a first device storing multiple sets of privacy data acquired from multiple persons and multiple reference features corresponding to the multiple sets of privacy data, where the multiple reference features each are expressed by an n-dimensional vector, includes receiving first encrypted features from a second device connected to the first device, generating multiple second converted features by a second conversion of the multiple reference features, generating of multiple second encrypted features by encrypting the multiple second converted features using inner product encryption, acquiring multiple inner product values by performing inner product computation of each of the first encrypted features and the multiple second encrypted features, determining whether or not the first features and the first reference features are similar, and transmitting of first privacy data corresponding to the first reference features out of the multiple sets of privacy data to the second device.

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Saitama, Japan

Nuttapong Attrapadung