Physical Tampering Detection Using Single COTS Wi-Fi Endpoint
| Autor: | Alexander I-Chi Lai, Ruey-Beei Wu, Poh Yuen Chan, Pei-Yuan Wu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
COTS Wi-Fi mobile device
Artificial neural network Orientation (computer vision) Computer science Chemical technology Real-time computing Detector Data_CODINGANDINFORMATIONTHEORY TP1-1185 channel state information (CSI) Biochemistry Article Atomic and Molecular Physics and Optics single embedded antenna Analytical Chemistry deep neural network (DNN) Channel state information physical tampering detection Neural Networks Computer False positive rate Electrical and Electronic Engineering Antenna (radio) Instrumentation True positive rate |
| Zdroj: | Sensors, Vol 21, Iss 5665, p 5665 (2021) Sensors Volume 21 Issue 16 Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | This paper proposes a practical physical tampering detection mechanism using inexpensive commercial off-the-shelf (COTS) Wi-Fi endpoint devices with a deep neural network (DNN) on channel state information (CSI) in the Wi-Fi signals. Attributed to the DNN that identifies physical tampering events due to the multi-subcarrier characteristics in CSI, our methodology takes effect using only one COTS Wi-Fi endpoint with a single embedded antenna to detect changes in the relative orientation between the Wi-Fi infrastructure and the endpoint, in contrast to previous sophisticated, proprietary approaches. Preliminary results show that our detectors manage to achieve a 95.89% true positive rate (TPR) with no worse than a 4.12% false positive rate (FPR) in detecting physical tampering events. |
| Databáze: | OpenAIRE |
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