Peeves: Physical Event Verification in Smart Homes
Simon Birnbach, Simon Eberz, Ivan Martinovic
Abstract
With the rising availability of smart devices (e.g., smart thermostats, lights, locks, etc.), they are increasingly combined into "smart homes". A key component of smart homes are event sensors that report physical events (such as doors opening or the light turning on) which can be triggered automatically by the system or manually by the user. However, data from these sensors are not always trustworthy. Both faults in the event sensors and involvement of active attackers can lead to reporting of events that did not physically happen (event spoong). This is particularly critical, as smart homes can trigger event chains (e.g., turning the radiator owhen a window is opened) without involvement of the user. The goal of this paper is to verify physical events using data from an ensemble of sensors (such as accelerometers or air pressure sensors) that are commonly found in smart homes. This approach both protects against event sensor faults and sophisticated attackers. In order to validate our system's performance, we set up a "smart home" in an oce environment. We recognize 22 event types using 48 sensors over the course of two weeks. Using data from the physical sensors, we verify the event stream supplied by the event sensors. We consider two threat models: a zero-eort attacker who spoofs events at arbitrary times and an opportunistic attacker who has access to a live stream of sensor data to better time their attack. We achieve perfect classication for 9 out of 22 events and achieve a 0% false alarm rate at a detection rate exceeding 99.9% for 15 events. We also show that even a strong opportunistic attacker is inherently limited to spoong few select events and that doing so involves lengthy waiting periods. CCS CONCEPTS • Security and privacy → Intrusion detection systems; Distributed systems security; Mobile and wireless security.
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