Arda Goknil, Ivan Kurtev, Leonard Tudorache, Adela Nedisan Videsjorden, Rustem Dautov, Hui Song, Dumitru Roman, Mihai Gheorghe, Ahmet Soylu
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引用次数: 0
Abstract
The rapid growth of Cyber-Physical Systems (CPS) has increased interest in digital twins (DTs) as virtual representations of physical systems to improve efficiency, monitoring, and security. However, as DTs become integral components of CPS, ensuring their own security also becomes critical. In this paper, we present a systematic literature review (SLR) on DTs and security for CPS. Following a standard SLR methodology, we defined three research questions, performed a structured search in four publication databases complemented by forward snowballing, applied inclusion and exclusion criteria, and extracted and synthesized data from the selected studies. The review examines both how DTs are used to enhance CPS security and how DTs themselves are secured within CPS. Our main results are: (i) a classification of CPS security challenges, threats, and vulnerabilities addressed using DTs; (ii) a mapping of security mechanisms, application domains, and emerging trends in using DTs for CPS security; (iii) a classification of DT security challenges, threats, and vulnerabilities across architectural, operational, data, and trust dimensions; (iv) a synthesis of state-of-the-art approaches for securing DTs; and (v) an analysis of open research problems and future directions for advancing both CPS security through DTs and the security of DTs themselves.
期刊介绍:
ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods.
ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.