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Moat: adaptive inside/outside detection system for smart homes

Moat: adaptive inside/outside detection system for smart homes
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.
Smart-home, Wi-Fi, inside/outside detection, location sensing
2474-9567
Wang, Chixiang
41c7b22c-4e95-4d25-a4c6-ecb84568129a
He, Weijia
f2223ad6-d8bd-4a98-8d6b-6ca8feef0a04
Pierson, Timothy J.
6e6805a3-cdac-475f-af11-3820371a5dc2
Kotz, David
0346c4a6-b7e9-4bb0-b00d-20b55d0b04ba
Wang, Chixiang
41c7b22c-4e95-4d25-a4c6-ecb84568129a
He, Weijia
f2223ad6-d8bd-4a98-8d6b-6ca8feef0a04
Pierson, Timothy J.
6e6805a3-cdac-475f-af11-3820371a5dc2
Kotz, David
0346c4a6-b7e9-4bb0-b00d-20b55d0b04ba

Wang, Chixiang, He, Weijia, Pierson, Timothy J. and Kotz, David (2024) Moat: adaptive inside/outside detection system for smart homes. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 8 (4), [157]. (doi:10.1145/3699751).

Record type: Article

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.

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More information

Published date: 21 November 2024
Keywords: Smart-home, Wi-Fi, inside/outside detection, location sensing

Identifiers

Local EPrints ID: 511636
URI: http://eprints.soton.ac.uk/id/eprint/511636
ISSN: 2474-9567
PURE UUID: 325d023f-445e-4779-964f-56299f434fdc
ORCID for Weijia He: ORCID iD orcid.org/0009-0002-1189-7063

Catalogue record

Date deposited: 26 May 2026 16:40
Last modified: 27 May 2026 02:10

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Contributors

Author: Chixiang Wang
Author: Weijia He ORCID iD
Author: Timothy J. Pierson
Author: David Kotz

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