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Privacy-Preserving Wi-Fi Fingerprinting Indoor Localization

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Abstract

A diversity of indoor localization techniques have become accurate and ready to use. A client first measures its location characteristics, and then calculates its location with the information provided by the localization server. However, this process may reveal the location information of the client or leak the area information stored on the server. This hinders the growth of indoor localization, but there are only a few solutions available in the literature. In this paper, we formulate an adversary model for fingerprint-based indoor localization techniques, and propose a cryptographic scheme to protect the privacy of both parties in a localization process. Our scheme utilizes the current Wi-Fi fingerprint based positioning techniques, including Gaussian radial basis functions and sigmoid kernels.

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Notes

  1. 1.

    Of course, a careful implementation is still required in order not to reveal extra information about user locations.

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Acknowledgement

Sherman Chow is supported by the Early Career Scheme and the Early Career Award (CUHK 439713), and General Research Funds (CUHK 14201914) of the Research Grants Council, University Grant Committee of Hong Kong. Ming Li is supported by US National Science Foundation grant (CNS-1566634).

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Authors and Affiliations

  1. Department of Information Engineering, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong

    Tao Zhang, Sherman S. M. Chow & Zhe Zhou

  2. Department of Computer Science and Engineering, University of Nevada, Reno, NV, 89557, USA

    Ming Li

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  1. Tao Zhang
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  2. Sherman S. M. Chow
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  3. Zhe Zhou
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  4. Ming Li
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Correspondence to Tao Zhang .

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Editors and Affiliations

  1. Japan Broadcasting Corporation, Tokyo, Japan

    Kazuto Ogawa

  2. Yokohama National University, Yokohama, Japan

    Katsunari Yoshioka

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Zhang, T., Chow, S.S.M., Zhou, Z., Li, M. (2016). Privacy-Preserving Wi-Fi Fingerprinting Indoor Localization. In: Ogawa, K., Yoshioka, K. (eds) Advances in Information and Computer Security. IWSEC 2016. Lecture Notes in Computer Science(), vol 9836. Springer, Cham. https://doi.org/10.1007/978-3-319-44524-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-44524-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44523-6

  • Online ISBN: 978-3-319-44524-3

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