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The lack of standard input interfaces in the Internet of Things (IoT)ecosystems presents a challenge in securing such infrastructures. To tacklethis challenge, we introduce a novel behavioral biometric system based onnaturally occurring interactions with objects in smart environments. Thisbiometric leverages existing sensors to authenticate users without requiringany hardware modifications of existing smart home devices. The system isdesigned to reduce the need for phone-based authentication mechanisms, on whichsmart home systems currently rely. It requires the user to approve transactionson their phone only when the user cannot be authenticated with high confidencethrough their interactions with the smart environment.  We conduct a real-world experiment that involves 13 participants in a companyenvironment, using this experiment to also study mimicry attacks on ourproposed system. We show that this system can provide seamless and unobtrusiveauthentication while still staying highly resistant to zero-effort, video, andin-person observation-based mimicry attacks. Even when at most 1% of thestrongest type of mimicry attacks are successful, our system does not requirethe user to take out their phone to approve legitimate transactions in morethan 80% of cases for a single interaction. This increases to 92% oftransactions when interactions with more objects are considered.

BeeHIVE: Behavioral Biometric System based on Object Interactions in Smart Environments