Abstract: A k-anonymization device includes: a list creation unit 1 that creates, based on generalization hierarchies about attribute values of attributes of a database, lists of values, each being obtained by generalizing each attribute value of each attribute of the database to each generalization level of the corresponding generalization hierarchy, and codes representing the values; a search unit 3 that searches for a node with k-anonymity of a lattice structure in parallel by determining whether a generalized database obtained by generalizing the database to generalization levels corresponding to each node of the lattice structure has k-anonymity based on the generalized database represented by the codes, which is obtained by referring to the created lists; and an output unit 4 that outputs a generalized database obtained by generalizing the database to generalization levels corresponding to a node with k-anonymity, which was found by the search, of the lattice structure.

Abstract: A random number generation apparatus comprises: a first random number generating part 2 generating a random number u=(u1, . . . ,uD)T?[??,?]D; a second random number generating part 3 generating a random number v?[0,f?max]; and a determining part 4 determining whether f?(x1=u1, . . . ,xD=uD)?v or not, and, if f?(x1=u1, . . . ,xD=uD)?v, adopting u as a random number according to f?(x1, . . . ,xD), wherein D is a predetermined positive integer, for i=1, . . . ,D, [hi] is a predetermined possible range for a random variable xi, a hole [h] is [h]=([h1], . . . ,[hD])T, H is a probability of a predetermined basic distribution function f(x1, . . . ,xD) in the hole [h], ?=1/(1?H), a corrected distribution function f?(x1, . . . ,xD) is defined by Expressions (1) and (2), and f?max is a maximum value of f?(x1, . . . ,xD).

Abstract: A synthetic data generation apparatus includes: a random number generating unit that generates first synthetic data with a ratio of a frequency distribution of each attribute being approximate to the ratio of the frequency distribution of that attribute in target data for which synthetic data is to be generated; and a data formatting unit that formats the first synthetic data using a matrix given by Cholesky decomposition of a variance-covariance matrix of the target data or a scaling matrix given by singular value decomposition of the variance-covariance matrix of the target data such that a mean vector and a correlation matrix of the first synthetic data agree with a mean vector and a correlation matrix of the target data and that a minimum and a maximum of the first synthetic data are present in ranges of a minimum and a maximum of the target data, and provides the first synthetic data after formatting as synthetic data.

Abstract: A synthetic data generation apparatus codes a value of each of category attributes contained in original data into a value of a numerical attribute in accordance with a coding rule; generates first synthetic data from the original data after coding using a synthetic data generation method for numerical attributes; if the value of the numerical attribute which is contained in the first synthetic data and corresponds to the value of one of the category attributes exceeds a range of values that can be assumed by the value of that numerical attribute, converts the value of that numerical attribute to a value included in the range of values that can be assumed by the value of that numerical attribute; and decodes the value of the numerical attribute which is contained in the first synthetic data after conversion and corresponds to the value of one of the category attributes to the value of that category attribute in accordance with the coding rule to obtain synthetic data.

Abstract: A k-anonymization device includes: a list creation unit 1 that creates, based on generalization hierarchies about attribute values of attributes of a database, lists of values, each being obtained by generalizing each attribute value of each attribute of the database to each generalization level of the corresponding generalization hierarchy, and codes representing the values; a search unit 3 that searches for a node with k-anonymity of a lattice structure in parallel by determining whether a generalized database obtained by generalizing the database to generalization levels corresponding to each node of the lattice structure has k-anonymity based on the generalized database represented by the codes, which is obtained by referring to the created lists; and an output unit 4 that outputs a generalized database obtained by generalizing the database to generalization levels corresponding to a node with k-anonymity, which was found by the search, of the lattice structure.