Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Privacy Protection Model for Location-Based Services

  • Ni, Lihao (National Engineering Research Center for E-Learning (NERCEL), Central China Normal University) ;
  • Liu, Yanshen (Hubei Research Center for Educational Informationization, Central China Normal University) ;
  • Liu, Yi (Hubei Research Center for Educational Informationization, Central China Normal University)
  • Received : 2018.06.08
  • Accepted : 2019.04.22
  • Published : 2020.02.29
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Abstract

Solving the disclosure problem of sensitive information with the k-nearest neighbor query, location dummy technique, or interfering data in location-based services (LBSs) is a new research topic. Although they reduced security threats, previous studies will be ineffective in the case of sparse users or K-successive privacy, and additional calculations will deteriorate the performance of LBS application systems. Therefore, a model is proposed herein, which is based on geohash-encoding technology instead of latitude and longitude, memcached server cluster, encryption and decryption, and authentication. Simulation results based on PHP and MySQL show that the model offers approximately 10× speedup over the conventional approach. Two problems are solved using the model: sensitive information in LBS application is not disclosed, and the relationship between an individual and a track is not leaked.

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