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The combination of smart home platforms and automation apps introduces muchconvenience to smart home users. However, this also brings the potential forprivacy leakage. If a smart home platform is permitted to collect all theevents of a user day and night, then the platform will learn the behaviorpatterns of this user before long. In this paper, we investigate how IFTTT, oneof the most popular smart home platforms, has the capability of monitoring thedaily life of a user in a variety of ways that are hardly noticeable. Moreover,we propose multiple ideas for mitigating privacy leakages, which altogetherforms a Filter-and-Fuzz (F&F) process: first, it filters out events unneeded bythe IFTTT platform; then, it fuzzes the values and frequencies of the remainingevents. We evaluate the F&F process, and the results show that the proposedsolution makes IFTTT unable to recognize any of the user's behavior patterns.

Privacy Leakage in Smart Homes and Its Mitigation: IFTTT as a Case Study