Patent ID: 8326849
Filing Date: 2012-12-04
Classification: G06F

Abstract:
1. A method of de-identifying a dataset containing personal data records to minimize data loss on a computing device comprising a memory and a processor, the processor performing the method comprising: retrieving the dataset from a storage device; determining equivalence classes for one or more quasi-identifiers defined within the dataset, the equivalence classes based upon ranges of values associated with each quasi-identifier; generating a lattice comprising a plurality of nodes, each node of the lattice defining an anonymization strategy by equivalence class generalization of one or more quasi-identifiers and an associated record suppression value, the plurality of nodes in the lattice arranged in rows providing monotonically decreasing level of suppression from a bottom of the lattice to a top of the lattice; generating a solution set for one or more generalization strategies for the plurality of nodes of the lattice providing k-anonymity, by performing a recursive binary search of the lattice commencing from a left most node in a middle row of the lattice, each of the one or more generalization strategies being defined by nodes lowest in the respective generalization strategy within the lattice, each providing a least amount of equivalence class generalization of one or more quasi-identifiers and the associated record suppression value of the dataset; and determining one or more optimal nodes from the solution set the one or more optimal nodes lowest in height in the one or more generalization strategies, the one or more optimal nodes providing the least amount of generalization and suppression within the solution set of one or more records of the dataset, the optimal nodes determined to provide minimal information loss using a non-uniform entropy metric.