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

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.

Keywords

query semantics / sensitive information / privacy protection / road networks / location based services

References

[1] Terrovitis M. Privacy preserving in the dissemination of location data. In: Proceedings of the 17th ACM International Conference on Knowledge Discovery and Data mining. 2011, 6–18

[2] Lin X, Hu H, Li P, Xu J, Choi B. Private proximity detection and monitoring with vicinity regions. In: Proceedings of the 12th International ACMWorkshop on Data Engineering forWireless and Mobile Access. 2013, 5–12

[3] Hu H, Xu J, Xu X, Pei K, Choi B, Zhou S. Private search on key-value stores with hierarchical indexes. In: Proceedings of the 30th IEEE International Conference on Data Engineering. 2014, 628–639

[4] Pan X, Meng X. Preserving location privacy without exact locations in mobile services. Frontiers of Computer Science, 2013, 7(3): 317–340

[5] Zhang X J, Meng X F. Discovering top-k patterns with differential privacy-an accurate approach. Frontiers of Computer Science, 2014, 8(5): 816–827

[6] Damiani M L, Bertino E, Silvestri C. The probe framework for the personalized cloaking of private locations. Transactions on Data Privacy, 2010, (3): 123–148

[7] Lee B, Oh J, Yu H, Kim J. Protecting location privacy using location semantics. In: Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2011

[8] Yigitoglu E, Damiani M, Abul O, Silvestri C. Privacy-preserving sharing of sensitive semantic locations under road-network constraints. In: Proceedings of the 13th International Conference onMobile DataManagement. 2012, 186–195

[9] Xiao Z, Xu J, Meng X. P-sensitivity: a semantic privacy-protection model for location-based services. In: Proceedings of the International Workshop on Privacy-Aware Location-based Mobile Services. 2008, 47–54

[10] Mouratidis K, Yiu M L. Anonymous query processing in road networks. IEEE Transactions on Knowledge and Data Engineering, 2009, 22(1): 2–15

[11] Gruteser M, Grunwald D. Anonymous usage of location-based services through spatial and temporal cloaking. In: Proceedings of the 1st International Conference on Mobile Systems, Applications and Services. 2003, 31–42

[12] Ghinita G, Damiani M, Silvestri C. Preventing velocity based linkage attacks in location-aware applications. In: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2009, 244–255

[13] Pan X, Xu J, Meng X. Protecting location privacy against locationdependent attacks in mobile services. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(8): 1506–1519

[14] Chow C, Mokbel M. Enabling privacy continuous queries for revealed user locations. In: Proceedings of the International Symposium on Advances in Spatial and Temporal Databases. 2007

[15] Pan X, Meng X, Xu J. Distortion-based anonymity for continuous queries in location-based mobile services. In: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2009, 256–265

[16] Hu H, Xu J, On S T, Du J, Ng J K Y. Privacy-aware location data publishing. Transactions on Database Systems, 2010, 35(3): 18

[17] Krishnamachari B, Ghinita G, Kalnis P. Privacy-preserving publication of user locations in the proximity of sensitive sites. In: Proceedings of International Conference on Scientific and Statistical Database Management. 2008, 95–113

[18] Gedik B, Liu L. Location privacy in mobile systems: a personalized anonymization model. In: Proceedings of the 25th IEEE International Conference on Distributed Computing Systems. 2005, 620–629

[19] Bamba B, Liu L, Pesti P, Wang T. Supporting anonymous location queries in mobile environments with privacygrid. In: Proceedings of the 17th International World Wide Web Conference. 2008, 237–246

[20] Xue M, Kalnis P, Pung H. Enhanced privacy protection in location based services. In: Proceedings of the 4th International Symposium on Location and Context Awareness. 2009, 70–87

[21] Liu F, Hua K. Protecting user privacy better with query l-diversity. International Journal of Information Security and Privacy, 2010, 4(2):1–18

[22] Gedik B, Liu L. Location privacy in mobile systems: a personalized anonymization model. In: Proceedings of the International Conference on Distributed Computing Systems. 2005, 620–629

[23] Kido H, Yanagisawa Y, Satoh T. Protection of location privacy using dummies for location-based services. In: Proceedings of the 21st International Conference on Data Engineering Workshops. 2005, 1248–1253

[24] Yiu M, Jensen C, Huang X, Lu H. Spacetwist: managing the trade-offs among location privacy, query performance, and query accuracy in mobile services. In: Proceedings of the 24th IEEE International Conference on Data Engineering. 2008, 366–375

[25] Khoshgozaran A, Shahabi C. Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy. In: Proceedings of the 10th International Conference on Advances in Spatial and Temporal Databases. 2007, 239–257

[26] Ghinita G, Kalnis P, Khoshgozaran A, Shahabi C, Tan K. Private queries in location based services: anonymizers are not necessary. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data. 2008, 121–132

[27] Wang T, Liu L. Privacy aware mobile services over road networks. In: Proceedings of the 45th International Conference on Very Large Data Bases. 2009

[28] Chow C, Mokbel M F, Bao J, Liu X. Query-aware location anonymization for road networks. Geoinformatical, 2010, 15(3): 571–607

[29] Ghinita G, Kalnis P, Skiadopoulos S. Prive: anonymous location-based queries in distributed mobile systems. In: Proceedings of the 16th International Conference on World Wide Web. 2007, 371–380

[30] Li P, Peng W, Wang T, Ku W. A cloaking algorithm based on spatial networks for location privacy. In: Proceedings of International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing. 2008, 90–97

[31] Pan X, Wu L, Hu Z, Huo Z. Voronoi-based spatial cloaking algorithm over road network. In: Proceedings of the 26th International Conference on Database and Expert Systems Applications. 2014, 273–280

[32] Palanisamy B, Liu L, Lee K, Singh A, Tang Y. Location privacy with road network mix-zones. In: Proceedings of the 8th IEEE International Conference on Mobile Ad-hoc and Sensor Networks. 2012, 124–131

[33] Palanisamy B, Ravichandran S, Liu L, Han B, Lee K, Pu C. Road network mix-zones for anonymous location based services. In: Proceedings of the 29th IEEE International Conference on Data Engineering. 2013, 1300–1303

[34] Palanisamy B, Liu L. Effective mix-zone anonymization techniques for mobile travelers. GeoInformatica, 2014, 135–164

[35] Palanisamy B, Liu L, Lee K, Meng S, Tang Y, Zhou Y. Anonymizing continuous queries with delay-tolerant mix-zones over road networks. Distributed and Parallel Databases, 2014, 91–118

[36] Mouratidis K, Yiu ML. Shortest path computation with no information leakage. In: Proceedings of the 38th International Conference on Very Large Data Bases. 2012, 24–36

[37] Li F, Cheng D, Hadjieleftheriou M, Kollios G, Teng S. On trip planning queries in spatial databases. In: Proceedings of the 9th International Symposium on Spatial and Temporal Databases. 2005, 273–290

[38] Xue J, Liu X, Yang X, Wang B. A location privacy preserving approach on road network. Chinese Joural of Computers, 2011, 34(5): 865–878

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg