Abstract
With the high demand of using location-based services (LBSs) in our daily lives, the privacy protection of users’ trajectories has become a significant concern. When users utilize LBSs, their location and trajectory information may expose their identities in continuous LBSs. Using the spatial and temporal correspondences on users’ trajectories, adversaries can easily gather their private information. Using collaboration between users instead of location service providers (LSPs) reduces the chance of revealing private information to adversaries. However, there is an assumption of a trusting relationship between peers. In this paper, we propose the trustworthy collaborative query-trajectory privacy-preserving (TCQTPP) scheme, which anonymizes users’ trajectories and resolves the untrustworthy relationship between users based on peer-to-region LBSs. Moreover, the TCQTPP scheme provides query content preservation based on a fake query concept in which we conceal the user’s actual query among a set of queries. The results of several experiments with different conditions confirm that our proposed scheme can protect users’ trajectory privacy successfully in a trustworthy and efficient manner.
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Murad, M., Altwaijri, S., Khabti, J., Baazeem, I., Tian, Y. (2022). Trustworthy Collaborative Trajectory Privacy Scheme for Continuous LBS. In: Tian, Y., Ma, T., Khan, M.K., Sheng, V.S., Pan, Z. (eds) Big Data and Security. ICBDS 2021. Communications in Computer and Information Science, vol 1563. Springer, Singapore. https://doi.org/10.1007/978-981-19-0852-1_12
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DOI: https://doi.org/10.1007/978-981-19-0852-1_12
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