Data Privacy Games

With the growing popularity of big data applications, data mining technologies has attracted more and more attention in recent years. In the meantime, the fact that data mining may bring serious threat to individual privacy has become a major concern. How to deal with the conflict between big data and individual privacy is an urgent issue. In this chapter, we review the privacy issues related to data mining in a systematic way, and investigate various approaches that can help to protect privacy. According to the basic procedure of data mining, we identify four different types of users involved in big data applications, namely data provider, data collector, data miner and decision maker. For each type of user, we discuss its privacy concerns and the methods it can adopt to protect sensitive information. Basics of related research topics are introduced, and state-of-the-art approaches are reviewed. We also present some preliminary thoughts on future research directions. Specifically, we emphasize the game theoretical approaches that are proposed for analyzing the interactions among different users in a data mining scenario. By differentiating the responsibilities of different users with respect to information security, we’d like to provide some useful insights into the trade-off between data exploration and privacy protection.