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Privacy-Aware Information Sharing in Location-Based Services: Attacks and Defense
Zhikai XU Hongli ZHANG Xiangzhan YU Shen SU
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2016/08/01
Online ISSN: 1745-1361
Type of Manuscript: Special Section PAPER (Special Section on Security, Privacy and Anonymity of Internet of Things)
location privacy, inference attack, privacy enhancing technology, location-based services, internet of things,
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Location-based services (LBSs) are useful for many applications in internet of things(IoT). However, LBSs has raised serious concerns about users' location privacy. In this paper, we propose a new location privacy attack in LBSs called hidden location inference attack, in which the adversary infers users' hidden locations based on the users' check-in histories. We discover three factors that influence individual check-in behaviors: geographic information, human mobility patterns and user preferences. We first separately evaluate the effects of each of these three factors on users' check-in behaviors. Next, we propose a novel algorithm that integrates the above heterogeneous factors and captures the probability of hidden location privacy leakage. Then, we design a novel privacy alert framework to warn users when their sharing behavior does not match their sharing rules. Finally, we use our experimental results to demonstrate the validity and practicality of the proposed strategy.