Digital Twins in Security Operations: State of the Art and Future Perspectives

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Philip Empl, David Koch, Marietheres Dietz, Günther Pernul
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引用次数: 0

Abstract

In an era of rapid technological advancements, digital twins are gaining attention in industry and research. These virtual representations of real-world entities, enabled by the Internet of Things (IoT), offer advanced simulation and analysis capabilities. Their application spans various sectors, from smart manufacturing to healthcare, highlighting their versatility. However, the rise of digital technologies has also escalated cybersecurity concerns. Historical cyberattacks underscore the urgency for enhanced security operations. In this context, digital twins represent a novel approach to cybersecurity. Industry and academic research are increasingly exploring their potential to protect their assets. Despite growing interest and applications, more comprehensive research synthesis needs to be done, particularly in security operations based on digital twins. Our paper aims to fill this gap through a structured literature review aggregating knowledge from 201 publications. We focus on defining the digital twin in cybersecurity, exploring its applications, and outlining implementations and challenges. To maintain transparency, our data is documented and is publicly available. This survey serves as a crucial guide for academic and industry stakeholders, fostering digital twins in security operations.
安全操作中的数字孪生:技术现状和未来展望
在技术飞速发展的时代,数字双胞胎在工业界和研究领域受到越来越多的关注。这些由物联网(IoT)实现的现实世界实体的虚拟表示,提供了先进的模拟和分析功能。它们的应用横跨各个领域,从智能制造到医疗保健,凸显了它们的多功能性。然而,数字技术的兴起也加剧了人们对网络安全的担忧。历史上的网络攻击凸显了加强安全行动的紧迫性。在这种背景下,数字孪生代表了一种新的网络安全方法。工业和学术研究越来越多地探索它们保护资产的潜力。尽管对数字孪生的兴趣和应用越来越多,但需要进行更全面的综合研究,特别是在基于数字孪生的安全操作方面。我们的论文旨在通过汇总201篇出版物的结构化文献综述来填补这一空白。我们专注于定义网络安全中的数字孪生,探索其应用,并概述实现和挑战。为了保持透明度,我们的数据被记录并公开提供。这项调查为学术和行业利益相关者提供了重要指导,促进了安全运营中的数字孪生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
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.
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