Mitigation of Odometer Fraud for In-Vehicle Security Using the Discrete Hartley Transform
| Autor: | Monica Gemo, Raimondo Giuliani, Gianmarco Baldini |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies Computer science Real-time computing Fast Fourier transform 0211 other engineering and technologies 020206 networking & telecommunications 02 engineering and technology Odometer Discrete Hartley transform Frequency domain 0202 electrical engineering electronic engineering information engineering Hall effect sensor Time domain Noise (video) |
| Zdroj: | UEMCON 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) |
| DOI: | 10.1109/uemcon51285.2020.9298039 |
| Popis: | Odometer fraud is a serious offense in the automotive sector and indicates the disconnection, resetting, or alteration of a vehicle’s odometer and the related sensor with the intent to change the number of miles/Kms indicated or recorded to report false information. This paper focuses specifically on the threat scenario where the odometer sensor (i.e., Hall Sensor) is manipulated or replaced to implement an odometer fraud. This paper proposes a technique to mitigate odometer fraud by performing a physical layer authentication of the Hall Sensor, which takes in consideration the limitation of the in-vehicle networks and microprocessors. In particular, the Discrete Hartley Transform (DHT) in combination with machine learning algorithms is used to perform the authentication on an experimental data set of 12 Hall Sensors, which has been collected by the authors. The results shows that features extracted with DHT have more discriminating power than the original time domain and the frequency domain representations based on the Fast Fourier Transform (FFT) especially in presence of noise. |
| Databáze: | OpenAIRE |
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