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Impact Analysis of Cyberattacks in Electric Propulsion Systems for Hybrid Tracked Vehicles Dept. Automotive Engineering, Clemson University, South Caro
- Format:
- Book
- Conference/Event
- Author/Creator:
- Muriithi, Grace, author.
- Conference Name:
- 2024 NDIA Michigan Chapter Ground Vehicle Systems Engineering and Technology Symposium (2024-08-13 : Novi, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2024
- Summary:
- In the age of advancing digitalization and integrating complex electronics within modern vehicles, hybrid tracked vehicles (HTVs) are increasingly becoming susceptible to cybersecurity threats. Particularly vulnerable are the control units, which have become prime targets for adversarial exploitation due to their pivotal role in vehicle functionality. To address these security concerns, this study demonstrates two distinct yet equally harmful scenarios using replay and DoS attacks to uncover and evaluate vulnerabilities within the Energy Management System (EMS) of HEVs. In the replay attack scenario, the adversary surreptitiously alters the SoC control messages emanating from the Battery Management System (BMS). The attack is calibrated to strategically time and sequence the message replays across various operational states using reinforcement learning, thereby maintaining apparent legitimacy within expected SoC ranges to evade detection. The DoS attack, however, presents a more direct threat by targeting the generator's revolution speed sensors. By compromising these sensors, the attack disrupts the generator and causes subsequent engine shutdowns, compelling the battery to singularly meet the vehicle's power supply demands. Formal attack models are developed and subsequently deployed on a simulated HTV platform within MATLAB/Simulink to analyze the impacts of these cyberattacks. The simulation results illustrate the impacts of the simulated cyberattacks, further reinforcing the importance of resilient and adaptive security measures for the control layer
- Notes:
- Vendor supplied data
- Publisher Number:
- 2024-01-4114
- Access Restriction:
- Restricted for use by site license
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