An analytical survey of cyber‐physical systems in water treatment and distribution: Security challenges, intrusion detection, and future directions

IF 17.7 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-07-04 DOI:10.1002/spy2.440
Qawsar Gulzar, Khurram Mustafa
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Abstract

Since the inception of the Industrial 4.0 revolution, industrial cyber‐physical systems (CPSs) have become integral to critical infrastructures and industrial sectors, including water treatment and distribution systems. Integrating physical and digital worlds has made communication systems within these plants—comprising actuators, sensors, and controllers—vulnerable to advanced cyber‐attacks. Safeguarding the nation's critical infrastructure has thus attracted significant interest from both academia and industry. This article thoroughly examines water treatment and distribution CPSs, detailing their architectural design, devices, applications, and security standards. It analyzes various cyber‐attacks and explores CPS security vulnerabilities and their detection and mitigation techniques. Additionally, it reviews the trends in machine learning (ML) and deep learning (DL) intrusion detection system (IDS) solutions, highlighting their advantages and disadvantages. The article evaluates current datasets and testbeds, identifying some of the best‐performing IDS algorithms tested on each dataset compared to previous research, which could serve as benchmarks in this field. Finally, it proposes data augmentation techniques to generate comprehensive datasets, identifies research gaps, and suggests potential improvements to enhance IDS performance.
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水处理和分配中的网络物理系统分析调查:安全挑战、入侵检测和未来方向
自工业 4.0 革命开始以来,工业网络物理系统 (CPS) 已成为包括水处理和分配系统在内的关键基础设施和工业部门不可或缺的组成部分。物理世界与数字世界的融合使得这些工厂内的通信系统(包括执行器、传感器和控制器)很容易受到高级网络攻击。因此,保护国家的关键基础设施引起了学术界和工业界的极大兴趣。本文深入研究了水处理和配水 CPS,详细介绍了它们的结构设计、设备、应用和安全标准。文章分析了各种网络攻击,探讨了 CPS 的安全漏洞及其检测和缓解技术。此外,文章还回顾了机器学习(ML)和深度学习(DL)入侵检测系统(IDS)解决方案的发展趋势,强调了它们的优缺点。文章评估了当前的数据集和测试平台,确定了与以前的研究相比,在每个数据集上测试的一些性能最佳的 IDS 算法,这些数据集可作为该领域的基准。最后,文章提出了生成综合数据集的数据增强技术,确定了研究空白,并提出了提高 IDS 性能的潜在改进建议。
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
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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