Anonymizing moving objects: how to hide a MOB in a crowd?

Moving object databases (MOD) have gained much interest in recent years due to the advances in mobile communications and positioning technologies. Study of MOD can reveal useful information (e.g., traffic patterns and congestion trends) that can be used in applications for the common benefit. In order to mine and/or analyze the data, MOD must be published, which can pose a threat to the location privacy of a user. Indeed, based on prior knowledge of a user’s location at several time points, an attacker can potentially associate that user to a specific moving object (MOB) in the published database and learn her position information at other time points. In this paper, we study the problem of privacy-preserving publishing of moving object database. Unlike in microdata, we argue that in MOD, there does not exist a fixed set of quasi-identifier (QID) attributes for all the MOBs. Consequently the anonymization groups of MOBs (i.e., the sets of other MOBs within which to hide) may not...

• Type: Conference
• Year: 2009
• Where: EDBT
• Authors: Roman Yarovoy, Francesco Bonchi, Laks V. S. Lakshmanan, Wendy Hui Wang
• Keywords: Anonymization Groups, Database, EDBT 2009, Object Database, Time Points