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DCA: The Advanced Privacy-Enhancing Schemes for Location-Based Services

  • Jiaxun Hua
  • Yu Liu
  • Yibin Shen
  • Xiuxia TianEmail author
  • Cheqing Jin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10988)

Abstract

With the popularity of Location-based Services, LBS providers have been obtaining more data, by analyzing which they may infer users’ real locations and patterns of behavior. Unfortunately, most previous schemes using k-anonymity can hardly resist such fiercer side information-based privacy attacks. To address existing problems, we design a novel metric to accurately measure the resulted privacy level. Additionally, Dual Cloaking Anonymity (DCA) and enhanced-DCA (enDCA) algorithms, which are based on our metric, are also proposed. The former (DCA) constructs a k-anonymity set via carefully selecting k-1 users according to various query probabilities of each area and correlations between users’ query preferences. Then, enDCA further employs caching and location blurring to enhance the privacy preservation. Evaluations show that our proposals can significantly improve the privacy level.

Keywords

LBS privacy k-anonymity Confusion degree 

Notes

Acknowledgment

Our research is supported by the National Key Research and Development Program of China (2016YFB1000905), NSFC (61772327, 61370101, 61532021, U1501252, U1401256 and 61402180), Shanghai Knowledge Service Platform Project (No. ZF1213), Shanghai Science and Technology Committee Grant (15110500700).

References

  1. 1.
    Andrés, M.E., et al.: Geo-indistinguishability: differential privacy for location-based systems. In: 2013 ACM SIGSAC, pp. 901–914 (2013)Google Scholar
  2. 2.
    Ghinita, G., Kalnis, P., Khoshgozaran, A., Shahabi, C., Tan, K.L.: Private queries in location based services: anonymizers are not necessary. In: ACM SIGMOD (2008)Google Scholar
  3. 3.
    Kido, H., Yanagisawa, Y., Satoh, T.: An anonymous communication technique using dummies for location-based services. In: ICPS, pp. 88–97 (2005)Google Scholar
  4. 4.
    Luo, W., Hengartner, U.: VeriPlace: a privacy-aware location proof architecture. In: ACM SIGSPATIAL GIS, pp. 23–32 (2010)Google Scholar
  5. 5.
    Mokbel, M.F., Chow, C.Y., Aref, W.G.: The new casper: query processing for location services without compromising privacy. In: VLDB, pp. 763–774 (2006)Google Scholar
  6. 6.
    Niu, B., Li, Q., Zhu, X., Cao, G.: Achieving k-anonymity in privacy-aware location-based services. In: IEEE INFOCOM, pp. 754–762 (2014)Google Scholar
  7. 7.
    Niu, B., Li, Q., Zhu, X., Cao, G.: Enhancing privacy through caching in location-based services. In: IEEE INFOCOM, pp. 1017–1025 (2015)Google Scholar
  8. 8.
    Okamoto, M., Fujita, N., Inomae, G., Tate, H.: Wi-Fi LBS: information delivery services using Wi-Fi access point location. NTT Tech. Rev. 11(9) (2013)Google Scholar
  9. 9.
    Palanisamy, B., Liu, L.: MobiMix: protecting location privacy with mix-zones over road networks. In: IEEE ICDE, pp. 494–505 (2011)Google Scholar
  10. 10.
    Papadopoulos, S., Bakiras, S., Papadias, D.: pCloud: a distributed system for practical PIR. IEEE TDSC 9(1), 115–127 (2012)Google Scholar
  11. 11.
    Shokri, R., Theodorakopoulos, G., Papadimitratos, P., Kazemi, E.: Hiding in the mobile crowd: locationprivacy through collaboration. IEEE TDSC 11(3), 266–279 (2014)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Jiaxun Hua
    • 1
  • Yu Liu
    • 1
  • Yibin Shen
    • 1
  • Xiuxia Tian
    • 3
    Email author
  • Cheqing Jin
    • 2
  1. 1.School of Computer Science and Software EngineeringEast China Normal UniversityShanghaiChina
  2. 2.School of Data Science and EngineeringEast China Normal UniversityShanghaiChina
  3. 3.Shanghai University of Electric PowerShanghaiChina

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