In pervasive computing environments, Location- Based Services (LBSs) arebecoming increasingly important due to continuous advances in mobile networksand positioning technologies. Nevertheless, the wide deployment of LBSs canjeopardize the location privacy of mobile users. Consequently, providingsafeguards for location privacy of mobile users against being attacked is animportant research issue. In this paper a new scheme for safeguarding locationprivacy is proposed. Our approach supports location K-anonymity for a widerange of mobile users with their own desired anonymity levels by clustering.The whole area of all users is divided into clusters recursively in order toget the Minimum Bounding Rectangle (MBR). The exact location information of auser is replaced by his MBR. Privacy analysis shows that our approach canachieve high resilience to location privacy threats and provide more privacythan users expect. Complexity analysis shows clusters can be adjusted in realtime as mobile users join or leave. Moreover, the clustering algorithms possessstrong robustness.
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