Citation

Boi B, Gupta T, Rinhel M, Jubea I, Khondoker R, Esposito C, Sousa BM. Vehicles (Basel) 2023; 5(4): 1760-1802.

Copyright

(Copyright © 2023, MDPI: Multidisciplinary Digital Publications Institute)

DOI

10.3390/vehicles5040096

PMID

unavailable

Abstract

The increasing usage of autonomous and automatic systems within the automotive industry is steering us towards a more interconnected world. This enhanced interconnectivity fosters a more streamlined driving experience, reduces costs, and provides timely driver assistance. The electric/electronic (EE) architectures of modern vehicles are inherently complex due to the multitude of components they encompass. Contemporary architectures reveal that these components converge at an electronic control unit (ECU) called the central gateway, which could potentially represent a single point of failure. While this central unit is typically adequately safeguarded, the same cannot be said for the connected components, which often remain vulnerable to cyber threats. The ISO/SAE 21434 standard paved the way for automotive cybersecurity and could be used in parallel with other standards such as ISO 26262 and ISO PAS 21488. Automatic collision notification (ACN) is one of the most typical systems in a vehicle, and limited effort has been dedicated to identifying the most suitable architecture for this feature. This paper addresses the existing security and privacy gap of this feature by conducting a comparative analysis of security threats in two distinct ACN architectures. Notably, despite ACN architectures exhibiting inherent similarities, the primary distinction between the two architectures lies in their strategies for crash estimation and detection, followed by subsequent communication with emergency response teams. A rigorous security assessment was conducted using the ISO/SAE 21434 standard, employing the TARA and STRIDE methodologies through the Ansys medini analyze software. This analysis identified an average of 310 threats per architecture, including a significant number of high-level threats (11.8% and 15%, respectively), highlighting the importance of a comprehensive evaluation.

Language: en

Keywords

automatic crash notification; internet of vehicles; ISO/SAE 21434; TARA