Table of Contents Author Guidelines Submit a Manuscript
Security and Communication Networks
Volume 2017, Article ID 4842694, 11 pages
https://doi.org/10.1155/2017/4842694
Research Article

An Efficient Context-Aware Privacy Preserving Approach for Smartphones

1Ministry of Education Key Laboratory for Modern Teaching Technology, Shaanxi Normal University, Xi’an 710119, China
2School of Computer Science, Shaanxi Normal University, Xi’an 710119, China
3Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA

Correspondence should be addressed to Xiaoming Wang; nc.ude.unns@mxgnaw

Received 11 March 2017; Accepted 12 April 2017; Published 27 April 2017

Academic Editor: Qing Yang

Copyright © 2017 Lichen Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. P. Corcoran, “Privacy in the age of the smartphone,” IEEE Potentials, vol. 35, no. 5, pp. 30–35, 2016. View at Publisher · View at Google Scholar
  2. J. Tsai, PG. Kelley, LF. Cranor, and N. Sadeh, “Location sharing technologies: privacy risks and controls,” I/S: A Journal of Law and Policy for the Information Society, vol. 6, no. 2, pp. 119–317, 2010. View at Google Scholar
  3. X. Zheng, Z. Cai, J. Li, and H. Gao, “Location-privacy-aware review publication mechanism for local business service systems,” in Proceedings of the 36th Annual IEEE International Conference on Computer Communications (INFOCOM '17), Atlanta, Ga, USA, 2017.
  4. W. Enck, P. Gilbert, B.-G. Chun et al., “Taint droid: an information flow tracking system for real-time privacy monitoring on smartphones,” Communications of the ACM, vol. 57, no. 3, pp. 99–106, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. E. Kim, S. Helal, and D. Cook, “Human activity recognition and pattern discovery,” IEEE Pervasive Computing, vol. 9, no. 1, pp. 48–53, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. A. Mannini and A. M. Sabatini, “Accelerometry-based classification of human activities using Markov modeling,” Computational Intelligence and Neuroscience, vol. 2011, Article ID 647858, 10 pages, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Götz, S. Nath, and J. Gehrke, “MaskIt: Privately releasing user context streams for personalized mobile applications,” in Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD '12), pp. 289–300, USA, May 2012. View at Publisher · View at Google Scholar · View at Scopus
  8. L. Zhang, Z. Cai, and X. Wang, “FakeMask: A Novel Privacy Preserving Approach for Smartphones,” IEEE Transactions on Network and Service Management, vol. 13, no. 2, pp. 335–348, 2016. View at Publisher · View at Google Scholar · View at Scopus
  9. W. Wang and Q. Zhang, “Privacy Preservation for Context Sensing on Smartphone,” IEEE/ACM Transactions on Networking, 2016. View at Publisher · View at Google Scholar · View at Scopus
  10. Z. He, Z. Cai, J. Yu, X. Wang, Y. Sun, and Y. Li, “Cost-efficient strategies for restraining rumor spreading in mobile social networks,” IEEE Transactions on Vehicular Technology, vol. 66, no. 3, pp. 2789–2800, 2017. View at Publisher · View at Google Scholar
  11. L. Zhang, X. Wang, J. Lu, P. Li, and Z. Cai, “An efficient privacy preserving data aggregation approach for mobile sensing,” Security and Communication Networks, vol. 9, 3844, no. 16, p. 3853, 2016. View at Publisher · View at Google Scholar · View at Scopus
  12. C. S. Jensen, H. Lu, and M. L. Yiu, “Location privacy techniques in client-server architectures,” in Privacy in Location-Based Applications, Lecture Notes in Computer Science, vol. 5599, pp. 31–58, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. M. Gruteser and D. Grunwald, “Anonymous usage of location-based services through spatial and temporal cloaking,” in Proceedings of the 1st International Conference on Mobile Systems, Applications and Services (MobiSys ’03), pp. 31–42, San Francisco, Calif, USA, May 2003. View at Publisher · View at Google Scholar
  14. A. R. Beresford, A. Rice, N. Skehin, and R. Sohan, “MockDroid: trading privacy for application functionality on smartphones,” in Proceedings of the 12th International Workshop on Mobile Computing Systems and Applications (HotMobile '11), pp. 49–54, ACM, Phoenix, Ariz, USA, March 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. P. Hornyack, S. Han, J. Jung, S. Schechter, and D. Wetherall, “These aren't the droids you're looking for: retrofitting android to protect data from imperious applications,” in Proceedings of the 18th ACM Conference on Computer and Communications Security (CCS '11), pp. 639–651, Chicago, Illinois, USA, October 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. K. Fawaz and K. G. Shin, “Location privacy protection for smartphone users,” in Proceedings of the 21st ACM Conference on Computer and Communications Security (CCS '14), pp. 239–250, USA, November 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. X. Wang, Y. Mu, and R. Chen, “One-round privacy-preserving meeting location determination for smartphone applications,” IEEE Transactions on Information Forensics and Security, vol. 11, no. 8, pp. 1712–1721, 2016. View at Publisher · View at Google Scholar · View at Scopus
  18. X. Zheng, Z. Cai, J. Yu, C. Wang, and Y. Li, “Follow but no track: privacy preserved profile publishing in cyber-physical social systems,” IEEE Internet of Things Journal, 2017. View at Publisher · View at Google Scholar
  19. X. Li, J. Yang, Z. Sun, and J. Zhang, “Differential privacy for edge weights in social networks,” Security and Communication Networks, vol. 2017, Article ID 4267921, 10 pages, 2017. View at Publisher · View at Google Scholar
  20. B. Gedik and L. Liu, “Location privacy in mobile systems: a personalized anonymization model,” in Proceedings of the 25th IEEE International Conference on Distributed Computing Systems (ICDCS '05), pp. 620–629, Columbus, Ohio, USA, 2005. View at Publisher · View at Google Scholar
  21. C. Reynold, Y. Zhang, E. Bertino, and S. Prabhakar, “Preserving user location privacy in mobile data management infrastructures,” in Proceedings of the 6th international conference on Privacy Enhancing Technologies (PET '06), G. Danezis and P. Golle, Eds., vol. 4258 of Lecture Notes in Computer Science, pp. 393–412, Springer, Cambridge, UK, 2006. View at Publisher · View at Google Scholar
  22. K. Vu, R. Zheng, and J. Gao, “Efficient algorithms for K-anonymous location privacy in participatory sensing,” in Proceedings of the 31st Annual IEEE International Conference on Computer Communications (INFOCOM '12), pp. 2399–2407, Orlando, Fla, USA, March 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. M. Gruteser and X. Liu, “Protecting privacy in continuous location-tracking applications,” IEEE Security & Privacy, vol. 2, no. 2, pp. 28–34, 2004. View at Publisher · View at Google Scholar · View at Scopus
  24. W. Wang and Q. Zhang, “A stochastic game for privacy preserving context sensing on mobile phone,” in Proceedings of the 33rd Annual IEEE International Conference on Computer Communications (INFOCOM '14), pp. 2328–2336, can, May 2014. View at Publisher · View at Google Scholar · View at Scopus
  25. J. Cappos, L. Wang, R. Weiss, Y. Yang, and Y. Zhuang, “BlurSense: dynamic fine-grained access control for smartphone privacy,” in Proceedings of the 9th IEEE Sensors Applications Symposium (SAS '14), pp. 329–332, Queenstown, New Zealand, February 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. L. Zhang, X. Wang, W. Dou, and X. Zhao, “Secure verifiable active access control for medical sensor networks,” Chinese Journal of Electronics, vol. 21, no. 3, pp. 555–558, 2012. View at Google Scholar · View at Scopus
  27. J. Abdella, M. Özuysal, and E. Tomur, “CA-ARBAC: privacy preserving using context-aware role-based access control on Android permission system,” Security and Communication Networks, vol. 9, no. 18, pp. 5977–5995, 2016. View at Publisher · View at Google Scholar
  28. F. Rahman, D. Williams, S. I. Ahamed, J.-J. Yang, and Q. Wang, “PriDaC: privacy preserving data collection in sensor enabled RFID based healthcare services,” in Proceedings of the IEEE 15th International Symposium on High-Assurance Systems Engineering (HASE '14), pp. 236–242, USA, January 2014. View at Publisher · View at Google Scholar · View at Scopus
  29. Z. Cai, Z. He, X. Guan, and Y. Li, “Collective data-sanitization for preventing sensitive information inference attacks in social networks,” IEEE Transactions on Dependable and Secure Computing, 2016. View at Publisher · View at Google Scholar
  30. H. Zhu, X. Liu, R. Lu, and H. Li, “Efficient and privacy-preserving online medical pre-diagnosis framework using nonlinear svm,” IEEE Journal of Biomedical and Health Informatics, 2016. View at Publisher · View at Google Scholar
  31. M. Han, J. Li, Z. Cai, and Q. Han, “Privacy reserved influence maximization in gps-enabled cyber-physical and online social networks,” in Proceedings of the IEEE International Conference on Social Computing and Networking (SocialCom '16), pp. 284–292, Atlanta, Ga, USA, October 2016. View at Publisher · View at Google Scholar
  32. M. Han, Q. Han, L. Li, J. Li, and Y. Li, “Maximizing influence in sensed heterogenous social network with privacy preservation,” International Journal of Sensor Networks, pp. 1–11, 2017. View at Google Scholar
  33. I. Bilogrevic, M. Jadliwala, V. Joneja, K. Kalkan, J.-P. Hubaux, and I. Aad, “Privacy-preserving optimal meeting location determination on mobile devices,” IEEE Transactions on Information Forensics and Security, vol. 9, no. 7, pp. 1141–1156, 2014. View at Publisher · View at Google Scholar · View at Scopus
  34. X. Wang, Y. Lin, Y. Zhao, L. Zhang, J. Liang, and Z. Cai, “A novel approach for inhibiting misinformation propagation in human mobile opportunistic networks,” Peer-to-Peer Networking and Applications, vol. 20, no. 2, pp. 337–394, 2016. View at Google Scholar · View at Scopus
  35. S. Gisdakis, V. Manolopoulos, S. Tao, A. Rusu, and P. Papadimitratos, “Secure and privacy-preserving smartphone-based traffic information systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 3, pp. 1428–1438, 2015. View at Publisher · View at Google Scholar · View at Scopus
  36. K. Grover, A. Lim, S. Lee, and Q. Yang, “Privacy-enabled probabilistic verification in broadcast authentication for vehicular networks,” Ad-Hoc and Sensor Wireless Networks, vol. 32, no. 3-4, pp. 239–274, 2016. View at Google Scholar · View at Scopus
  37. N. Eagle and A. Pentland, “Reality mining: sensing complex social systems,” Personal and Ubiquitous Computing, vol. 10, no. 4, pp. 255–268, 2006. View at Publisher · View at Google Scholar · View at Scopus