Novel Privacy Preserving Method of Countering the Threats from Priori Knowledge
Weijia Yang, Shang-Teng Huang · 2009
Recently, many data anonymization methods have been proposed to protect privacy in the applications of data mining. But few of them have considered the threats from user's priori knowledge of data patterns. To solve this problem, a flexible method was proposed to randomize the dataset, so that the user could hardly obtain the sensitive data even knowing data relationships in advance. The method also achieves a high level of accuracy in the mining process as demonstrated in the experiments.