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Protecting personalized privacy against sensitivity homogeneity attacks over road networks in mobile services

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Abstract

Privacy preservation has recently received considerable attention for location-based mobile services. A lot of location cloaking approaches focus on identity and location protection, but few algorithms pay attention to prevent sensitive information disclosure using query semantics. In terms of personalized privacy requirements, all queries in a cloaking set, from some user’s point of view, are sensitive. These users regard the privacy is breached. This attack is called as the sensitivity homogeneity attack. We show that none of the existing location cloaking approaches can effectively resolve this problem over road networks. We propose a (K, L, P)-anonymity model and a personalized privacy protection cloaking algorithm over road networks, aiming at protecting the identity, location and sensitive information for each user. The main idea of our method is first to partition users into different groups as anonymity requirements. Then, unsafe groups are adjusted by inserting relaxed conservative users considering sensitivity requirements. Finally, segments covered by each group are published to protect location information. The efficiency and effectiveness of the method are validated by a series of carefully designed experiments. The experimental results also show that the price paid for defending against sensitivity homogeneity attacks is small.

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Authors and Affiliations

  1. Schod of Economics and Management, Shijiazhuang Tiedao University, Shijiazhuang, 050043, China

    Xiao Pan, Weizhang Chen, Lei Wu, Chunhui Piao & Zhaojun Hu

Authors
  1. Xiao Pan
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  2. Weizhang Chen
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  3. Lei Wu
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  4. Chunhui Piao
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  5. Zhaojun Hu
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Corresponding author

Correspondence to Lei Wu.

Additional information

Xiao Pan is an associate professor at Shijiazhuang Tiedao University, China, and a member of the Soft Science Research Institute on Engineering and Construction Management, China. She is a visiting scholar in the Department of Computer Science, University of Illinois at Chicago, USA. She received her PhD in Computer Science from Renmin University of China in 2010. Her research interests include data management on moving objects, location based social networks and privacy-aware computing.

Weizhang Chen is a master student at Shijiazhuang Tiedao University, China in 1992. He received his BS from Shijiazhuang Tiedao University in 2014. His research interests include data management on moving objects and privacyaware computing.

Lei Wu is a lecturer at Shijiazhuang Tiedao University, China. He received hisMS in Computer Science from Yanshan University, China in 2007. His research interests include data management on moving objects, location based social networks and privacyaware computing.

Chunhui Piao is a professor at Shijiazhuang Tiedao University, China. She received her PhD in Computer Science from Renmin University of China in 2012. Her research interests include electronic commerce and big data management.

Zhaojun Hu is a junior student in School of Economics and Management at Shijiazhuang Tiedao University, China. Her research interests include data management on moving objects and privacy-aware computing.

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Pan, X., Chen, W., Wu, L. et al. Protecting personalized privacy against sensitivity homogeneity attacks over road networks in mobile services. Front. Comput. Sci. 10, 370–386 (2016). https://doi.org/10.1007/s11704-015-4528-9

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  • DOI: https://doi.org/10.1007/s11704-015-4528-9

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