CLPP: Context-aware location privacy protection for location-based social network

Location-based social network (LBSN) has grown exponentially over the past several years. Given its high utility value, LBSN, however, has raised serious concerns about users' location privacy. Although users may avoid releasing geo-content in sensitive locations, this, however, does not necessarily prevent the adversary from inferring users' privacy through spatial-temporal correlations and historical information. In this paper, we introduce a new location privacy problem: context-aware location privacy protection (CLPP) problem where the privacy requirements of users are not constant and isolated. We propose a novel metric to quantify the privacy risks. Then the CLPP is formalized as how to accurately and efficiently evaluate whether the users' published geo-content meet the user's privacy requirement. To achieve online evaluating, we design two novel algorithms to calculate the correlation between the locations. Eventually, our experimental results demonstrate the validity and practicality of the proposed strategy.