Patent ID: 9355258
Filing Date: 2016-05-31
CPC Classification: G06F

Claim Text:
1. A database privacy protection method comprising: determining, via one or more processors, a distribution pattern of one or more database attributes by applying Kurtosis measurement of data corresponding to the attributes to ascertain whether the distribution pattern is leptokurtic; determining, via the one or more processors, an adversary information gain for a k-anonymity data sanitization model and adversary information gain for a k-anonymity l-diversity data sanitization model, wherein the adversary information gain is the difference between entropy of S and a conditional entropy H(S|Q), and wherein S corresponds to a set of the attributes; comparing, via the one or more processors, the adversary information gain of the k-anonymity data sanitization model with the adversary information gain of the k-anonymity l-diversity data sanitization model repeatedly until the adversary information gain of the k-anonymity data sanitization model equals the adversary information gain of the k-anonymity l-diversity data sanitization model; determining, via the one or more processors, an optimal value of l for performing l-diversity based data sanitization on database records related to the attributes and an optimal value of k for performing k-anonymity based data sanitization on the attributes; and performing, via the one or more processors, privacy preservation of the attributes by only k-anonymity data sanitization model when k is greater than l and the distribution pattern is leptokurtic.