NDLI: Privacy Protection against Query Prediction in Location-Based Services

Content Provider	IEEE Xplore Digital Library
Author	Zhengang Wu Liangwen Yu Jiawei Zhu Huiping Sun Zhi Guan Zhong Chen
Copyright Year	2014
Description	Author affiliation: Inst. of Software, Peking Univ., Beijing, China (Zhengang Wu; Jiawei Zhu; Huiping Sun; Zhi Guan; Zhong Chen) \|\| Nat. Comput. Emergency Response Team & Coordination Center, China (Liangwen Yu)
Abstract	In mobile Internet, Location-Based Services (LBSs) as a popular kind of context-aware recommendation systems can recommend Point of Interest (POI) data according to current locations of users. However, the inherent feature leads to leak sensitive location information of users into untrusted LBS providers. This paper aims at the location privacy problem on query prediction which forecasts next locations and violates user privacy seriously. To tackle this, we propose a novel location privacy protection solution. The contribution is three-fold. First, we model query prediction on cloaking regions using the Bayesian inference. Next, the proposed location anonymization method can generalize locations into safer cloaking regions against such query prediction attacks. Finally, a series of experiments evaluate the performance of this solution and demonstrate its availability.
Starting Page	525
Ending Page	532
File Size	335136
Page Count	8
File Format	PDF
e-ISBN	9781479976461
DOI	10.1109/UIC-ATC-ScalCom.2014.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-09
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Privacy Data privacy Conferences Predictive models Location Cloaking Location Prediction Bayesian Inference Entropy Location Privacy Protection Trajectory Cloaking Regions
Content Type	Text
Resource Type	Article

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