Moat: Adaptive Inside/Outside Detection System for Smart Homes

Smart-home technology is now pervasive, demanding increased attention to the security of the devices and the privacy of the home's residents. To assist residents in making security and privacy decisions - e.g., whether to allow a new device to connect to the network, or whether to be alarmed when an unknown device is discovered - it helps to know whether the device is inside the home, or outside. In this paper we present MOAT, a system that leverages Wi-Fi sniffers to analyze the physical properties of a device's wireless transmissions to infer whether that device is located inside or outside of a home. MOAT can adaptively self-update to accommodate changes in the home indoor environment to ensure robust long-term performance. Notably, MOAT does not require prior knowledge of the home's layout or cooperation from target devices, and is easy to install and configure. We evaluated MOAT in four different homes with 21 diverse commercial smart devices and achieved an overall balanced accuracy rate of up to 95.6%. Our novel periodic adaptation technique allowed our approach to maintain high accuracy even after rearranging furniture in the home. MOAT is a practical and efficient first step for monitoring and managing devices in a smart home.

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Institutions

Publication Details

Journal
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Published
2024-11-21
DOI
https://doi.org/10.1145/3699751
Citations
20
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
4.17

Funders

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article

Moat: Adaptive Inside/Outside Detection System for Smart Homes

Timothy J. Pierson, Weijia He, Chixiang Wang, David Kotz
20 citations
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
IoT-based Smart Home Systems
4.17
article

Moat: Adaptive Inside/Outside Detection System for Smart Homes

Timothy J. Pierson, Weijia He, Chixiang Wang, David Kotz
article en
20 citations

Abstract

Smart-home technology is now pervasive, demanding increased attention to the security of the devices and the privacy of the home's residents. To assist residents in making security and privacy decisions - e.g., whether to allow a new device to connect to the network, or whether to be alarmed when an unknown device is discovered - it helps to know whether the device is inside the home, or outside. In this paper we present MOAT, a system that leverages Wi-Fi sniffers to analyze the physical properties of a device's wireless transmissions to infer whether that device is located inside or outside of a home. MOAT can adaptively self-update to accommodate changes in the home indoor environment to ensure robust long-term performance. Notably, MOAT does not require prior knowledge of the home's layout or cooperation from target devices, and is easy to install and configure. We evaluated MOAT in four different homes with 21 diverse commercial smart devices and achieved an overall balanced accuracy rate of up to 95.6%. Our novel periodic adaptation technique allowed our approach to maintain high accuracy even after rearranging furniture in the home. MOAT is a practical and efficient first step for monitoring and managing devices in a smart home.

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous TechnologiesVol. 8(4)
Dartmouth College (US), University of Southampton (GB)
Engineering and Physical Sciences Research Council
Sustainable cities and communities
Openalex Percentile: Top 5%
IoT-based Smart Home Systems
4.17
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