4.7 Article

Cyber-Physical Security of Energy-Efficient Powertrain System in Hybrid Electric Vehicles Against Sophisticated Cyberattacks

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TTE.2020.3022713

Keywords

Computer security; Transportation; Batteries; Mechanical power transmission; Engines; Torque; Hybrid electric vehicles (HEVs); sophisticated attacks; vehicle cyber– physical security; vehicle powertrain systems; vulnerability assessment

Funding

  1. National Science Foundation [ECCS-1946057]

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This article presents an innovative approach to improving the cyber-physical security of energy-efficient powertrain system in HEVs against sophisticated cyberattacks. Three levels of attack taxonomy are considered, with a focus on long-term sophisticated cyberattacks that can potentially cause severe damages. Innovative evaluation metrics and a probability-based detection method are proposed for comprehensive vulnerability assessment and improvement of cyber-physical security.
In this article, an innovative approach to improving the cyber-physical security of energy-efficient powertrain system in a hybrid electric vehicle (HEV) against sophisticated cyberattacks is presented. To the best of our knowledge, cyberattacks, especially sophisticated and subtle cyberattacks, have not yet been studied in energy management systems (EMSs) for HEVs. First of all, we present a systemic assessment of long-term sophisticated cyberattacks that aim to deteriorate the battery lifetime and energy efficiency of HEVs. Specifically, three levels of attack taxonomy according to the skill level of the attackers are considered, which are sophisticated and can hardly be detected by the human driver. In addition to levels 1 and 2, cyberattacks that do not or partially require prior knowledge of the vehicle, and we explore two other types of level 3 damage-oriented controller attacks made by highly skilled attackers who have sufficient knowledge of the system. Such sophisticated attacks will potentially cause severe damages, such as decreasing battery capacity and energy by up to 50%. For a comprehensive vulnerability assessment, we propose innovative evaluation metrics to analyze the impact and stealthiness of sophisticated attacks. Finally, a preliminary probability-based detection method for sophisticated damage-oriented controller attacks is developed to improve the cyber-physical security of energy-efficient powertrain system in HEVs.

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