Potential Attacks against k-Anonymity on LBS and Solutions for Defending the Attacks
Widespread using of mobile positioning devices makes location based service (LBS) more and more popular. Since LBS need users’ current location and some of users’ personal interest as input, it would incurs some privacy related issues about the users. One important and comparatively effective method to protect users’ privacy in LBS is spatial cloaking based on k-anonymity, however there are some inherent drawbacks of traditional k-anonymity techniques in protecting users’ privacy in LBS. In this paper, we analysis some security attacks that utilized these drawbacks to encroach users’ privacy in LBS, and then we proposed some novel methods to defend these attacks. At the end, some suggestions for constructing a security scheme to protect the users’ privacy in using LBS are given.
KeywordsLBS privacy k-anonymity continuous queries distribution inference K-disaccord
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