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.
@article{arxiv.1808.07379,
title = {Privacy Mining from IoT-based Smart Homes},
author = {Ming-Chang Lee and Jia-Chun Lin and Olaf Owe},
journal= {arXiv preprint arXiv:1808.07379},
year = {2018}
}
Comments
This paper, which has 11 pages and 7 figures, has been accepted BWCCA 2018 on 13th August 2018