DALP: A demand-aware location privacy protection scheme in continuous location-based services

• Published in: Concurrency and computation Vol. 28; no. 4; pp. 1219 - 1236
• Main Authors: Li, Xinghua, Wang, Ermeng, Yang, Weidong, Ma, Jianfeng
• Format: Journal Article
• Language: English
• Published: Blackwell Publishing Ltd 25.03.2016
• Subjects: Algorithms; Constraining; continuous LBS queries; Customizing; Demand; location privacy protection; location-based service; Location-based services; Privacy; QoS; Queries; User requirements
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.3613

Summary Location‐based services (LBSs) via mobile handheld devices have been subject to major privacy concerns for users. Currently, most of the existing works concerning the continuous LBS queries mainly focus on users' privacy demands with little consideration of the service of quality (QoS). In this paper, we propose a demand‐aware location protection scheme for continuous LBS requests, allowing a user to customize not only location privacy but also QoS requirement, while this results that in considerably many queries points, the privacy and QoS requirement cannot be met together, and the location privacy protection cannot be provided for the continuous LBS queries. We point out that its underlying reason is that in few LBS query regions, the footprints are sparse or the privacy requirements are set unreasonably high. Therefore, a maximum demands‐aware query sequence algorithm is proposed in the scheme. Through identifying and restraining the queries in those regions, most of LBS queries are satisfied; thus, the longest LBS query sequence is obtained, which can satisfy a user's specific privacy and QoS requirements simultaneously. Furthermore, on the premise that the user's privacy requirement is met, in demand‐aware location protection scheme, we propose two algorithms to minimize the constructed cloaking regions, reducing the query latency and the server's workload and providing better QoS for users. Extensive simulations on a large dataset prove the effectiveness of our approach under various location privacy and QoS demands. Copyright © 2015 John Wiley & Sons, Ltd.