Beyond Anonymity in Location Based Services

This paper presents ongoing research on privacy issues in emerging data management applications. Current approaches to privacy preservation in location based services (LBS) have focused on anonymization techniques based on the spatio-temporal generalization of requests. These techniques prevent the identification of the issuer of a request among a group of potential issuers that happen to be in the same generalized region. In these approaches the only parameter characterizing the level of anonymity is the cardinality k of the group of potential issuers. Our research shows that when requests from multiple users for multiple services are considered, there are other important parameters affecting the ability of the attacker to identify an issuer. In this paper we investigate in particular the parameter characterizing the diversity of requested services and its relationship with the anonymity provided by request generalization.