TY - JOUR
T1 - Integrated Attack Tree in Residual Risk Management Framework
AU - Khan, Ahmed Nawaz
AU - Bryans, Jeremy
AU - Sabaliauskaite, Giedre
AU - Jadidbonab, Hesamaldin
N1 - This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
PY - 2023/11/29
Y1 - 2023/11/29
N2 - Safety-critical cyber-physical systems (CPSs), such as high-tech cars having cyber capabilities, are highly interconnected. Automotive manufacturers are concerned about cyber attacks on vehicles that can lead to catastrophic consequences. There is a need for a new risk management approach to address and investigate cybersecurity risks. Risk management in the automotive domain is challenging due to technological improvements and advances every year. The current standard for automotive security is ISO/SAE 21434, which discusses a framework that includes threats, associated risks, and risk treatment options such as risk reduction by applying appropriate defences. This paper presents a residual cybersecurity risk management framework aligned with the framework presented in ISO/SAE 21434. A methodology is proposed to develop an integrated attack tree that considers multiple sub-systems within the CPS. Integrating attack trees in this way will help the analyst to take a broad perspective of system security. Our previous approach utilises a flow graph to calculate the residual risk to a system before and after applying defences. This paper is an extension of our initial work. It defines the steps for applying the proposed framework and using adaptive cruise control (ACC) and adaptive light control (ALC) to illustrate the applicability of our work. This work is evaluated by comparing it with the requirements of the risk management framework discussed in the literature. Currently, our methodology satisfies more than 75% of their requirements.
AB - Safety-critical cyber-physical systems (CPSs), such as high-tech cars having cyber capabilities, are highly interconnected. Automotive manufacturers are concerned about cyber attacks on vehicles that can lead to catastrophic consequences. There is a need for a new risk management approach to address and investigate cybersecurity risks. Risk management in the automotive domain is challenging due to technological improvements and advances every year. The current standard for automotive security is ISO/SAE 21434, which discusses a framework that includes threats, associated risks, and risk treatment options such as risk reduction by applying appropriate defences. This paper presents a residual cybersecurity risk management framework aligned with the framework presented in ISO/SAE 21434. A methodology is proposed to develop an integrated attack tree that considers multiple sub-systems within the CPS. Integrating attack trees in this way will help the analyst to take a broad perspective of system security. Our previous approach utilises a flow graph to calculate the residual risk to a system before and after applying defences. This paper is an extension of our initial work. It defines the steps for applying the proposed framework and using adaptive cruise control (ACC) and adaptive light control (ALC) to illustrate the applicability of our work. This work is evaluated by comparing it with the requirements of the risk management framework discussed in the literature. Currently, our methodology satisfies more than 75% of their requirements.
KW - automotive cybersecurity
KW - risk management framework
KW - risk assessment
KW - attack tree
KW - ISO/SAE 21434
UR - http://www.scopus.com/inward/record.url?scp=85180552348&partnerID=8YFLogxK
U2 - 10.3390/info14120639
DO - 10.3390/info14120639
M3 - Article
SN - 2078-2489
VL - 14
JO - Information
JF - Information
IS - 12
M1 - 639
ER -