Privacy Mining from IoT-based Smart Homes
This addresses privacy risks for elders in smart homes, but it is incremental as it applies existing mining techniques to a new domain.
The paper tackles the problem of privacy disclosure in IoT-based smart homes for elders by introducing a Privacy Mining Approach (PMA) that deduces sensor topology and house layouts from sensor datasets, demonstrating the severity of the issue.
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.