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Physical Tampering Detection Using Single COTS Wi-Fi Endpoint
| Content Provider | MDPI |
|---|---|
| Author | Chan, Poh Yuen Lai, Alexander I-Chi Wu, Pei-Yuan Wu, Ruey-Beei |
| Copyright Year | 2021 |
| Description | 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. |
| Starting Page | 5665 |
| e-ISSN | 14248220 |
| DOI | 10.3390/s21165665 |
| Journal | Sensors |
| Issue Number | 16 |
| Volume Number | 21 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-08-23 |
| Access Restriction | Open |
| Subject Keyword | Sensors Industrial Engineering Information and Library Science Physical Tampering Detection Channel State Information (csi) Cots Wi-fi Mobile Device Deep Neural Network (dnn) Single Embedded Antenna |
| Content Type | Text |
| Resource Type | Article |
