A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services

Zhang, Shaobo; Li, Xiong; Tan, Zhiyuan; Peng, Tao; Wang, Guojun

Abstract

With the rapid pervasion of location-based services (LBSs), protection of location privacy has become a significant concern. In most continuous LBSs' privacy-preserving solutions, users need to transmit the location query data to an untrusted location service provider (LSP) to obtain query results, and the users discard these results immediately after using them. This results in an ineffective use of these results by future queries and in turn leads to a higher risk to user privacy from the LSP. To address these issues, we generally use caching to cache the query results for users' future queries. However, the minimization of the interaction between users and LSPs is a challenge. In this paper, we propose an enhanced user privacy scheme through caching and spatial K-anonymity (CSKA) in continuous LBSs; it adopts multi-level caching to reduce the risk of exposure of users' information to untrusted LSPs. In continuous LBS queries, our scheme first utilizes the Markov model to predict the next query location according to the user mobility. Then, according to the predicted location, cell's cache contribution rate, and data freshness, an algorithm for forming spatial K-anonymity is designed to improve the user's cache hit rate and enhance the user location privacy. The security analysis and simulation results demonstrate that our proposed CSKA scheme can provide higher privacy protection than a few previous methods, and it can minimize the overhead of the LBS server.

Citation

Zhang, S., Li, X., Tan, Z., Peng, T., & Wang, G. (2019). A caching and spatial K-anonymity driven privacy enhancement scheme in continuous location-based services. Future Generation Computer Systems, 94, 40-50. https://doi.org/10.1016/j.future.2018.10.053

• Journal Article Type: Article
• Acceptance Date: Oct 29, 2018
• Online Publication Date: Nov 22, 2018
• Publication Date: 2019-05
• Deposit Date: Nov 1, 2018
• Publicly Available Date: Nov 22, 2018
• Journal: Future Generation Computer Systems
• Print ISSN: 0167-739X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 94
• Pages: 40-50
• DOI: https://doi.org/10.1016/j.future.2018.10.053
• Keywords: Location privacy, multi-level caching, spatial K-anonymity, user mobility, cache hit rate,
• Public URL: http://researchrepository.napier.ac.uk/Output/1332066