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Privacy Mining from IoT-Based Smart Homes

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Advances on Broadband and Wireless Computing, Communication and Applications (BWCCA 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 25))

Abstract

Recently, a wide range of smart devices are deployed in a variety of environments to improve the quality of human life. One of the important IoT-based applications is smart homes for healthcare, especially for elders. IoT-based smart homes enable elders’ health to be properly monitored and taken care of. However, elders’ privacy might be disclosed from smart homes due to non-fully protected network communication or other reasons. To demonstrate how serious this issue is, we introduce in this paper a Privacy Mining Approach (PMA) to mine privacy from smart homes by conducting a series of deductions and analyses on sensor datasets generated by smart homes. The experimental results demonstrate that PMA is able to deduce a global sensor topology for a smart home and disclose elders’ privacy in terms of their house layouts.

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Acknowledgments

This work is supported by the project IoTSec – Security in IoT for Smart Grids, with number 248113/O70 part of the IKTPLUSS program funded by the Norwegian Research Council. This work is also partially supported by SIRIUS, which is a Norwegian Centre for Research-driven Innovation in Norway. The authors would like to thank the anonymous reviewers for their valuable comments and suggestions that improve the paper quality.

Author information

Authors and Affiliations

  1. Department of Communication Systems, Simula Research Laboratory, Martin Linges vei 25, 1364, Fornebu, Norway

    Ming-Chang Lee

  2. Department of Informatics, University of Oslo, Gaustadallèen 23 B, 0373, Oslo, Norway

    Jia-Chun Lin & Olaf Owe

Authors
  1. Ming-Chang Lee
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  2. Jia-Chun Lin
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  3. Olaf Owe
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Corresponding authors

Correspondence to Ming-Chang Lee , Jia-Chun Lin or Olaf Owe .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Tunghai University, Taichung, Taiwan

    Fang-Yie Leu

  3. Rissho University, Tokyo, Japan

    Tomoya Enokido

  4. Asia University, Taichung, Taiwan

    Hsing-Chung Chen

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Lee, MC., Lin, JC., Owe, O. (2019). Privacy Mining from IoT-Based Smart Homes. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_27

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  • DOI: https://doi.org/10.1007/978-3-030-02613-4_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02612-7

  • Online ISBN: 978-3-030-02613-4

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