Using location-labeling for privacy protection in Location-Based Services

D. Liao, H. Li, V. Anand, V. Chang, G. Sun, H. Yu

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    The developments in positioning and mobile communication technology have made applications that use location-based services (LBS) increasingly popular. For privacy reasons and due to lack of trust in the LBS provider, k-anonymity and l-diversity techniques have been widely used to preserve user privacy in distributed LBS architectures. However, in reality, there exist scenarios where the user locations are identical or similar/near each other. In such a scenario the k locations selected by k-anonymity technique are the same and location privacy can be easily compromised or leaked. To address the issue of privacy protection, in this paper, we propose the concept of location-labels to distinguish mobile user locations to sensitive locations and ordinary locations. We design a location-label based (LLB) algorithm for protecting location privacy while minimizing the query response time of LBS. We also evaluate the performance and validate the correctness of the proposed algorithm through extensive simulations. Copyright © 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.
    Original languageEnglish
    Title of host publicationIoTBD 2016 - Proceedings of the International Conference on Internet of Things and Big Data
    EditorsVictor Chang, M Ramachandran, V. M. Munoz, G Wills, R Walters
    Publication statusPublished - 25 Apr 2016
    EventInternational Conference on Internet of Things and Big Data 2016 - Rome, Italy
    Duration: 23 Apr 201625 Apr 2016


    ConferenceInternational Conference on Internet of Things and Big Data 2016
    Abbreviated titleIoTBD 2016


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