earticle

논문검색

Perceived K-value Location Privacy Protection Method Based on LBS in Augmented Reality

원문정보

초록

영어

In Augmented Reality (AR), users’ main concern includes privacy and safety of data. Since location based services(LBS) are one of the major applications of the AR, it is important to have a privacy-aware management of location information, providing location privacy for clients against vulnerabilities or abuse. Here we analyzed the merit and demerit of exiting location privacy protection method. Then a perceived K-value location privacy protection method was raised. Hereafter the protocol of this algorithm was described and simulated in detail. The results demonstrated this method can effectively realize the location privacy protection.

목차

Abstract
 1. Introduction
 2. Way of Location Privacy Leak
 3. Related Works
 4. Comparison of the Existing Location Privacy Protection Method
  4.1 Pseudo-location Method
  4.2 Pseudonym Method
  4.3 k-anonymity Method
  4.4 Other Methods based on the k-anonymity Method
  4.5 Personalized k-anonymity Method
 5. Perceived K-value Location Privacy Protection Method
  5.1 The Analysis of Location Privacy Protection Level
  5.2 Algorithms and Procedure
  5.3 Experiment Simulation and Analysis of Algorithm Efficiency
 6. Conclusion
 Acknowledgments
 References

저자정보

  • Yang Yang Department of Information Technology, Nanjing Radio and TV University, Nanjing City Vocational College, Nanjing, Jiangsu 210002, China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.