2 research outputs found
A Clustering-based Location Privacy Protection Scheme for Pervasive Computing
In pervasive computing environments, Location- Based Services (LBSs) are
becoming increasingly important due to continuous advances in mobile networks
and positioning technologies. Nevertheless, the wide deployment of LBSs can
jeopardize the location privacy of mobile users. Consequently, providing
safeguards for location privacy of mobile users against being attacked is an
important research issue. In this paper a new scheme for safeguarding location
privacy is proposed. Our approach supports location K-anonymity for a wide
range of mobile users with their own desired anonymity levels by clustering.
The whole area of all users is divided into clusters recursively in order to
get the Minimum Bounding Rectangle (MBR). The exact location information of a
user is replaced by his MBR. Privacy analysis shows that our approach can
achieve high resilience to location privacy threats and provide more privacy
than users expect. Complexity analysis shows clusters can be adjusted in real
time as mobile users join or leave. Moreover, the clustering algorithms possess
strong robustness.Comment: The 3rd IEEE/ACM Int Conf on Cyber, Physical and Social Computing
(CPSCom), IEEE, Hangzhou, China, December 18-20, 201