Privacy Protection Model for Location-Based Services

Lihao Ni, Yanshen Liu, Yi Liu, Journal of Information Processing Systems Vol. 16, No. 1, pp. 96-112, Feb. 2020  

Keywords: Geohash-Encoding, Location-Based Services, Memcached Server Cluster, Point of Interest, Privacy ProtectionModel


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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Cite this article
[APA Style]
Ni, L., Liu, Y., & Liu, Y. (2020). Privacy Protection Model for Location-Based Services. Journal of Information Processing Systems, 16(1), 96-112. DOI: 10.3745/JIPS.04.0163.

[IEEE Style]
L. Ni, Y. Liu, Y. Liu, "Privacy Protection Model for Location-Based Services," Journal of Information Processing Systems, vol. 16, no. 1, pp. 96-112, 2020. DOI: 10.3745/JIPS.04.0163.

[ACM Style]
Lihao Ni, Yanshen Liu, and Yi Liu. 2020. Privacy Protection Model for Location-Based Services. Journal of Information Processing Systems, 16, 1, (2020), 96-112. DOI: 10.3745/JIPS.04.0163.