Detecting and Handling IoT Interaction Threats in Multi-Platform Multi-Control-Channel Smart Homes

Authors: 

Haotian Chi, Shanxi University and Temple University; Qiang Zeng, George Mason University; Xiaojiang Du, Stevens Institute of Technology

Abstract: 

A smart home involves a variety of entities, such as IoT devices, automation applications, humans, voice assistants, and companion apps. These entities interact in the same physical environment, which can yield undesirable and even hazardous results, called IoT interaction threats. Existing work on interaction threats is limited to considering automation apps, ignoring other IoT control channels, such as voice commands, companion apps, and physical operations. Second, it becomes increasingly common that a smart home utilizes multiple IoT platforms, each of which has a partial view of device states and may issue conflicting commands. Third, compared to detecting interaction threats, their handling is much less studied. Prior work uses generic handling policies, which are unlikely to fit all homes. We present IoTMediator, which provides accurate threat detection and threat-tailored handling in multi-platform multi-control-channel homes. Our evaluation in two real-world homes demonstrates that IoTMediator significantly outperforms prior state-of-the-art work.

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BibTeX
@inproceedings {287119,
author = {Haotian Chi and Qiang Zeng and Xiaojiang Du},
title = {Detecting and Handling {IoT} Interaction Threats in {Multi-Platform} {Multi-Control-Channel} Smart Homes},
booktitle = {32nd USENIX Security Symposium (USENIX Security 23)},
year = {2023},
isbn = {978-1-939133-37-3},
address = {Anaheim, CA},
pages = {1559--1576},
url = {https://www.usenix.org/conference/usenixsecurity23/presentation/chi},
publisher = {USENIX Association},
month = aug
}

Presentation Video