Privacy preservation in the dissemination of location data. SIGKDD Explorations Full text

Manolis Terrovitis
SIGKDD Explorations, 13(1), 2011.

The rapid advance in handheld communication devices and the appearance of smartphones has allowed users to connect to the Internet and surf on the WWW while they are moving around the city or traveling. Location based services have been developed to deliver content that is adjusted to the current user location. Social networks have also responded to the challenge of users who can access the Internet from any place in the city, and location based social-networks like Foursquare have become very popular in a short period of time. The popularity of these applications is linked to the significant advantages they offer: users can exploit live location-based information to take dynamic decisions on issues like transportation, identification of places of interest or even on the opportunity to meet a friend or an associate in nearby locations. A side effect of sharing location-based information is that it exposes the user to substantial privacy related threats. Revealing the user's location carelessly can prove to be embarrassing, harmful professionally, or even dangerous.

Research in the data management field has put significant effort on anonymization techniques that obfuscate spatial information in order to hide the identity of the user or her exact location. Privacy guaranties and anonymization algorithms become increasingly sophisticated offering better and more efficient protection in data publishing and data exchange. Still, it is not clear yet what are the greatest dangers to user privacy and which are the most realistic privacy breaching scenarios. The aim of the paper is to provide a brief survey of the attack scenarios, the privacy guaranties and the data transformations employed to protect user privacy in real time. The paper focuses mostly on providing an overview of the privacy models that are investigated in literature and less on the algorithms and their scaling capabilities. The models and the attack scenarios are classified and compared, in order to provide an overview of the cases that are covered by existing research.