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: Purchase from sellers of selection is enabled to be made through simple operations. Furthermore, prospective purchase events are distributed to sellers as needed. Demands of purchase candidates are retrieved.

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: A prediction model conversion method includes: converting a prediction model by converting at least one parameter which is included in the prediction model and is for performing homogenization processing into at least one parameter for performing processing including nonlinear processing, the prediction model being a neural network; and generating an encrypted prediction model that performs prediction processing with input in a secret state remaining secret by encrypting the prediction model that has been converted.

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 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: Purchase from sellers of selection is enabled to be made through simple operations. Furthermore, prospective purchase events are distributed to sellers as needed. Demands of purchase candidates are retrieved.

Abstract: Provided is a two-dimensional code structured in such a way that the identification function for each of multiple components constituting the two-dimensional code, which have been concatenated and encoded in the form of structured append, has been enhanced. In a set of multiple two-dimensional codes that have been encoded in the form of structured append, wherein the two-dimensional code comprises an information area, an illustration area, and a parity area, each two-dimensional code which is a component of the set of multiple two-dimensional codes is a two-dimensional code having the same graphical illustration drawn in the illustration area.

Abstract: A management apparatus reduces the number of pieces of unique information each not generated from another piece of unique information, among unique information being bases of keys assigned to managed apparatuses. The management apparatus calculates, for nodes in layers other than tree structure leaves, subsets of apparatus identifiers subordinate to the nodes, searches for a subset wholly containing another subset in the lowermost layer other than a leaf layer from an immediately-upper layer and mutually associates these subsets, searches for another subset wholly containing the containing subset from a same or an immediately-upper layer and mutually associates these subsets, controls this processing to repeat up to the uppermost layer, controls these processings to repeat on all subsets in the lowermost layer, makes unique information correspond to subsets in the lowermost layer, and makes information derivatively obtained from the unique information correspond to subsets connected due to the associating.

Abstract: A management apparatus reduces the number of pieces of unique information each not generated from another piece of unique information, among unique information being bases of keys assigned to managed apparatuses. The management apparatus calculates, for nodes in layers other than tree structure leaves, subsets of apparatus identifiers subordinate to the nodes, searches for a subset wholly containing another subset in the lowermost layer other than a leaf layer from an immediately-upper layer and mutually associates these subsets, searches for another subset wholly containing the containing subset from a same or an immediately-upper layer and mutually associates these subsets, controls this processing to repeat up to the uppermost layer, controls these processings to repeat on all subsets in the lowermost layer, makes unique information correspond to subsets in the lowermost layer, and makes information derivatively obtained from the unique information correspond to subsets connected due to the associating.