Earticle

초록

영어

Due to the advances of mobile devices with GPS (Global Positioning System), a user's privacy threat is increased in location based services (LBSs).So, various Location Privacy-Preserving Mechanisms (LPPMs) have been proposed in the literature to address the privacy risks derived from the exposure of user locations through the use of LBSs. However, these methods obfuscate the locations disclosed to the LBS provider using a variety of strategies, most of which come at a cost of resource consumption. Therefore, we propose a privacy-protected KNN query anonymization method based on Bayesian estimation for Location-based services. Unlike previous dummy-based approaches, in our method, the request to the LBS server doesn't contain the genuine user location, so we can't calculate whether meet the threshold condition of two location directly, but must to decision making by transition probability. In addition, our method just requires the server returns the results the client needs. Further, we propose an effective search algorithm to improve the server processing. So it can reduce bandwidth usages and efficiently support K-nearest neighbor queries without revealing the private information of the query issuer. An empirical study shows that our proposal is effective in terms of offering location privacy, and efficient in terms of computation and communication costs.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Proposed Method
  3.1 Definitions and Assumptions
  3.2. Privacy-Area Dummy Generation Algorithms
  3.3. Anonymity Query
  3.4. Server-Side Processing
  3.5. Communication Cost Analysis
 4. Performance Analysis
  4.1. Setting for Evaluation
  4.2. Communication Cost
  4.3. Server-Side Cost
  4.4. Result Accuracy Rate
  4.5. Anonymous Area Achieving Variance
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Huan Zhao [ School of Information Science and Engineering, Hunan University, Changsha, China ]
• Jiaolong Wan [ School of Information Science and Engineering, Hunan University, Changsha, China ]
• Zuo Chen [ School of Information Science and Engineering, Hunan University,Changsha, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605