Abstract
Quantifying location privacy is an interesting and hot topic in Location-Based Services (LBSs). However, existing schemes only consider the privacy leakage to the untrusted LBS servers, leaving out the leakage during the transportation phase. In this paper, we propose a privacy-preserving scheme to help the LBS user to select optimal privacy strategy with considering the aforementioned problem for the first time. In order to measure the efficacy of different kinds of Privacy-Preserving Mechanisms (PPMs) including cryptographic and non-cryptographic types, we first quantify the revenue of two kinds of aforementioned PPMs by considering the privacy loss and privacy leakage probability on the channel and LBS server, as well as the accumulated leakage previously, simultaneously. Then, we take the consumption of different PPMs into account, to compute the investment. Evaluation results illustrate the effectiveness and efficiency of our proposed scheme.
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Acknowledgement
This work was supported by the General Program of National Natural Science Foundation of China (61672515), the National Key Research and Development Program of China (2016YFB0800303) and the National Natural Science Foundation of China (61502489).
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Li, F., Liu, J., Fang, L., Niu, B., Geng, K., Li, H. (2017). Pricing Privacy Leakage in Location-Based Services. In: Ma, L., Khreishah, A., Zhang, Y., Yan, M. (eds) Wireless Algorithms, Systems, and Applications. WASA 2017. Lecture Notes in Computer Science(), vol 10251. Springer, Cham. https://doi.org/10.1007/978-3-319-60033-8_36
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DOI: https://doi.org/10.1007/978-3-319-60033-8_36
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