A data search method of a first device that includes a memory storing a plurality of sets of privacy data acquired from a plurality of persons and a plurality of reference features corresponding to the plurality of sets of privacy data, the plurality of reference features each being expressed by an n-dimensional vector, the method comprising: receiving first encrypted features from a second device connected to the first device via a communication network, the first encrypted features having been generated by encrypting first converted features, the first converted features having been generated by a first conversion of first features extracted from privacy data of a user, the first encrypted features having been generated by encrypting the first converted features using inner product encryption, the first features being expressed by an n-dimensional vector, and the first converted features being expressed by an n-dimensional vector; generating a plurality of second converted features by a second conversion of the plurality of reference features; generating a plurality of second encrypted features by encrypting the plurality of second converted features using inner product encryption; acquiring a plurality of inner product values by performing inner product computation of each of the first encrypted features and the plurality of second encrypted features; determining, when a first inner product value of the plurality of inner product values is not greater than a predetermined threshold value, and the first inner product value indicates a Euclidean distance between the first features and first reference features out of the plurality of reference features, that the first features and the first reference features are similar; and transmitting first privacy data corresponding to the first reference features out of the plurality of sets of privacy data to the second device, wherein the first features are subjected to the first conversion and the plurality of reference features are subjected to the second conversion so that a product of an i-dimensional component, where i ≤ n, of the first converted features and an i-dimensional component of each of the plurality of second converted features form a polynomial following unfolding of the Euclidean distance between the first features and the plurality of reference features. receiving first encrypted features from a second device connected to the first device via a communication network, the first encrypted features having been generated by encrypting first converted features, the first converted features having been generated by a first conversion of first features extracted from privacy data of a user, the first encrypted features having been generated by encrypting the first converted features using inner product encryption, the first features being expressed by an n-dimensional vector, and the first converted features being expressed by an n-dimensional vector; generating a plurality of second converted features by a second conversion of the plurality of reference features; generating a plurality of second encrypted features by encrypting the plurality of second converted features using inner product encryption; acquiring a plurality of inner product values by performing inner product computation of each of the first encrypted features and the plurality of second encrypted features; determining, when a first inner product value of the plurality of inner product values is not greater than a predetermined threshold value, and the first inner product value indicates a Euclidean distance between the first features and first reference features out of the plurality of reference features, that the first features and the first reference features are similar; and transmitting first privacy data corresponding to the first reference features out of the plurality of sets of privacy data to the second device, wherein the first features are subjected to the first conversion and the plurality of reference features are subjected to the second conversion so that a product of an i-dimensional component, where i ≤ n, of the first converted features and an i-dimensional component of each of the plurality of second converted features form a polynomial following unfolding of the Euclidean distance between the first features and the plurality of reference features.