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Article

Security-Related Hardware Cost Optimization for CAN FD-Based Automotive Cyber-Physical Systems

1
School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2
School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China
*
Author to whom correspondence should be addressed.
Academic Editors: Tian Wang, Geyong Min and Md Zakirul Alam Bhuiyan
Sensors 2021, 21(20), 6807; https://doi.org/10.3390/s21206807
Received: 2 September 2021 / Revised: 6 October 2021 / Accepted: 11 October 2021 / Published: 13 October 2021
(This article belongs to the Special Issue Fog/Edge Computing based Smart Sensing System)
The introduction of various networks into automotive cyber-physical systems (ACPS) brings great challenges on security protection of ACPS functions, the auto industry recommends to adopt the hardware security module (HSM)-based multicore ECU to secure in-vehicle networks while meeting the delay constraint. However, this approach incurs significant hardware cost. Consequently, this paper aims to reduce security enhancing-related hardware cost by proposing two efficient design space exploration (DSE) algorithms, namely, stepwise decreasing-based heuristic algorithm (SDH) and interference balancing-based heuristic algorithm (IBH), which explore the task assignment, task scheduling, and message scheduling to minimize the number of required HSMs. Experiments on both synthetical and real data sets show that the proposed SDH and IBH are superior than state-of-the-art algorithm, and the advantage of SDH and IBH becomes more obvious as the increase about the percentage of security-critical tasks. For synthetic data sets, the hardware cost can be reduced by 61.4% and 45.6% averagely for IBH and SDH, respectively; for real data sets, the hardware cost can be reduced by 64.3% and 54.4% on average for IBH and SDH, respectively. Furthermore, IBH is better than SDH in most cases, and the runtime of IBH is two or three orders of magnitude smaller than SDH and state-of-the-art algorithm. View Full-Text
Keywords: automotive cyber-physical systems; hardware cost; design space exploration algorithm; cyber security; CAN FD automotive cyber-physical systems; hardware cost; design space exploration algorithm; cyber security; CAN FD
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MDPI and ACS Style

Xie, Y.; Guo, Y.; Yang, S.; Zhou, J.; Chen, X. Security-Related Hardware Cost Optimization for CAN FD-Based Automotive Cyber-Physical Systems. Sensors 2021, 21, 6807. https://doi.org/10.3390/s21206807

AMA Style

Xie Y, Guo Y, Yang S, Zhou J, Chen X. Security-Related Hardware Cost Optimization for CAN FD-Based Automotive Cyber-Physical Systems. Sensors. 2021; 21(20):6807. https://doi.org/10.3390/s21206807

Chicago/Turabian Style

Xie, Yong, Yili Guo, Sheng Yang, Jian Zhou, and Xiaobai Chen. 2021. "Security-Related Hardware Cost Optimization for CAN FD-Based Automotive Cyber-Physical Systems" Sensors 21, no. 20: 6807. https://doi.org/10.3390/s21206807

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