| Author: | Li, Tianqi |
| Title: | Status-aware intrusion detection for in-vehicle networks |
| Advisors: | Luo, Xiapu (COMP) |
| Degree: | M.Sc. |
| Year: | 2021 |
| Subject: | Motor vehicles Motor vehicles -- Dynamics Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Computing |
| Pages: | xix, 74 pages : color illustrations |
| Language: | English |
| Abstract: | Most modern vehicles are equipped with many ECUs (Electronic Control Units) for better connectivity, controllability and human-machine interface. However, it creates new attack surfaces and the risks of software bugs and hardware glitches. In this project, we present a new anomaly detection method, which utilises three detection models to detect any anomaly in brake, steer and throttle (accelerator-pedal). We focus on the brake, steer and throttle, because they the main actuators, which have instantaneous impacts on the safety of vehicle dynamical states. We fist develop the three anomaly detection models, then we evaluate the effectiveness of these models. Our evaluation results show the safety of the related vehicle dynamical states can be effectively enforced. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 5824.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 5.72 MB | Adobe PDF | View/Open |
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