부산대학교 도서관

Keywords Cyber ship; Cyber physical systems (CPS); STPA; Cyber risk assessment; STRIDE; CORAS Abstract The widespread use of software-intensive cyber systems in critical infrastructures such as ships (CyberShips) has brought huge benefits, yet it has also opened new avenues for cyber attacks to potentially disrupt operations. Cyber risk assessment plays a vital role in identifying cyber threats and vulnerabilities that can be exploited to compromise cyber systems. Understanding the nature of cyber threats and their potential risks and impact is essential to improve the security and resilience of cyber systems, and to build systems that are secure by design and better prepared to detect and mitigate cyber attacks. A number of methodologies have been proposed to carry out these analyses. This paper evaluates and compares the application of three risk assessment methodologies: system theoretic process analysis (STPA-Sec), STRIDE and CORAS for identifying threats and vulnerabilities in a CyberShip system. We specifically selected these three methodologies because they identify threats not only at the component level, but also threats or hazards caused due to the interaction between components, resulting in sets of threats identified with each methodology and relevant differences. Moreover, STPA-Sec, which is a variant of the STPA, is widely used for safety and security analysis of cyber physical systems (CPS); CORAS offers a framework to perform cyber risk assessment in a top-down approach that aligns with STPA-Sec; and STRIDE (Spoofing, Tampering, Repudiation,Information disclosure, Denial of Service, Elevation of Privilege) considers threat at the component level as well as during the interaction that is similar to STPA-Sec. As a result of this analysis, this paper highlights the pros and cons of these methodologies, illustrates areas of special applicability, and suggests that their complementary use as threats identified through STRIDE can be used as an input to CORAS and STPA-Sec to make these methods more structured. Author Affiliation: (a) Business Management Department, Oregon Institute of Technology, Klamath Falls, OR 97601, United states (b) Digitalization Group, Rigshospitalet, Denmark (c) Department of Applied Mathematics & Computer Science, Technical University of Denmark, Kgs. Lyngby, DK-2800, Denmark (d) DTU Management Engineering, Technical University of Denmark, DK-2800, Kgs. Lyngby, Denmark * Corresponding author. Article History: Received 15 December 2022; Revised 13 February 2023; Accepted 8 March 2023 Byline: Rishikesh Sahay [rishikesh.sahay@oit.edu] (a), D.A. Sepulveda Estay [daniel.alberto.sepulveda.estay@regionh.dk] (b), Weizhi Meng [weme@dtu.dk] (*,c), Christian D. Jensen [cdje@dtu.dk] (c), Michael Bruhn Barfod [mbba@dtu.dk] (d)