Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.contributor.advisor | Luo, Xiapu (COMP) | en_US |
| dc.creator | Li, Tianqi | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/11386 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Status-aware intrusion detection for in-vehicle networks | en_US |
| dcterms.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. | en_US |
| dcterms.extent | xix, 74 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2021 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Motor vehicles | en_US |
| dcterms.LCSH | Motor vehicles -- Dynamics | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
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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