Privacy Leakage in Smart Homes and Its Mitigation: IFTTT as a Case Study
It addresses privacy risks for smart home users, but the mitigation approach is incremental.
The paper investigates privacy leakage in smart homes through IFTTT, showing it can monitor user behavior patterns, and proposes a Filter-and-Fuzz process that prevents IFTTT from recognizing any patterns.
The combination of smart home platforms and automation apps introduces much convenience to smart home users. However, this also brings the potential for privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which altogether forms a Filter-and-Fuzz (F&F) process: first, it filters out events unneeded by the IFTTT platform; then, it fuzzes the values and frequencies of the remaining events. We evaluate the F&F process, and the results show that the proposed solution makes IFTTT unable to recognize any of the user's behavior patterns.