Abstract: 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.

Abstract: An encryption processing system includes: a first device; second devices; and a third device, wherein the first device generates synthesis keys by selecting public keys of the second devices; generates an intermediate text from confidential texts generated by encrypting secret information by using public keys of the second devices having decryption authority; generates ciphertexts by further encrypting the intermediate text using the synthesis keys; and makes public the ciphertexts, each of the second devices verifies validity of the ciphertexts; generates decryption key fragments by using an own private key; and makes public the decryption key fragments, the third device verifies validity of the decryption key fragments; generates a decryption key by combining decryption key fragments; generates the Intermediate text by decrypting one of the ciphertexts; and makes public the intermediate text, and the second device decrypts the intermediate text using the own private key; and restores the secret information.

Abstract: 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.

Abstract: An encryption processing system includes: a first device; second devices; and a third device, wherein the first device generates synthesis keys by selecting public keys of the second devices; generates an intermediate text from confidential texts generated by encrypting secret information by using public keys of the second devices having decryption authority; generates ciphertexts by further encrypting the intermediate text using the synthesis keys; and makes public the ciphertexts, each of the second devices verifies validity of the ciphertexts; generates decryption key fragments by using an own private key; and makes public the decryption key fragments, the third device verifies validity of the decryption key fragments; generates a decryption key by combining decryption key fragments; generates the Intermediate text by decrypting one of the ciphertexts; and makes public the intermediate text, and the second device decrypts the intermediate text using the own private key; and restores the secret information.

Abstract: 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.

Abstract: A master key generation device generates a master public key and a master secret key. A user key generation device generates a user public key and a user secret key by using the master public key. An administration device acquires an arithmetic procedure. A data save unit saves data encrypted with the user public key as encryption data. The administration device selects, from the data save unit, encryption data which has been encrypted from data to be used for the arithmetic procedure. The administration device performs homomorphic operation on the encryption data based on the arithmetic procedure, and outputs the operation result of the homomorphic operation as an encryption operation result. A master decryption device acquires the encryption operation result, and decrypts the acquired encryption operation result with the master secret key.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A search system has a management device that stores compound data and a searcher device. The management device defines a similarity between query sequence data q representing a substructure or property of a substance that is input as a search condition at the searcher device and sequence data pi (i=1, 2, . . . , m) for substances stored in the database by means of a score T that takes a non-negative value when a Tversky index Si is greater than or equal to a threshold value ?n/?d (where ?n and ?d are natural numbers that satisfy ?n??d), calculates an encrypted value of the score T while the query sequence q is maintained in an encrypted state, and returns the encrypted value to the searcher device to thereby disclose information regarding whether or not similar compounds are present in the database while in a confidential state.

Abstract: A search system has a management device that stores compound data and a searcher device. The management device defines a similarity between query sequence data q representing a substructure or property of a substance that is input as a search condition at the searcher device and sequence data pi (i=1, 2, . . . , m) for substances stored in the database by means of a score T that takes a non-negative value when a Tversky index Si is greater than or equal to a threshold value ?n/?d (where ?n and ?d are natural numbers that satisfy ?n??d, calculates an encrypted value of the score T while the query sequence q is maintained in an encrypted state, and returns the encrypted value to the searcher device to thereby disclose information regarding whether or not similar compounds are present in the database while in a confidential state.

Abstract: A digital signature system comprises a center computer and a first and second terminal devices which can communicate with each other. The center computer generates and outputs a signing-key for a signer and a verification-key for a verifier. The first terminal device accepts the signing-key, generates a digital signature for a digital data to be signed using the signing-key, and outputs the digital signature. The second terminal device accepts the verification-key, the signer's identification code (e.g. the unique code of the signer), an identification code of the digital data and the digital signature, and verifies the validity of the digital signature using the verification-key, the identification code of the digital data and the signer's identification code.

Abstract: A digital signature system comprises a center computer and a first and second terminal devices which can communicate with each other. The center computer generates and outputs a signing-key for a signer and a verification-key for a verifier. The first terminal device accepts the signing-key, generates a digital signature for a digital data to be signed using the signing-key, and outputs the digital signature. The second terminal device accepts the verification-key, the signer's identification code (e.g. the unique code of the signer), an identification code of the digital data and the digital signature, and verifies the validity of the digital signature using the verification-key, the identification code of the digital data and the signer's identification code.