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المؤلفBhamare, D.
المؤلفZolanvari, M.
المؤلفErbad, A.
المؤلفJain, R.
المؤلفKhan, K.
المؤلفMeskin, Nader
تاريخ الإتاحة2022-04-14T08:45:39Z
تاريخ النشر2020
اسم المنشورComputers and Security
المصدرScopus
المعرّفhttp://dx.doi.org/10.1016/j.cose.2019.101677
معرّف المصادر الموحدhttp://hdl.handle.net/10576/29775
الملخصIndustrial Control System (ICS) is a general term that includes supervisory control & data acquisition (SCADA) systems, distributed control systems (DCS), and other control system configurations such as programmable logic controllers (PLC). ICSs are often found in the industrial sectors and critical infrastructures, such as nuclear and thermal plants, water treatment facilities, power generation, heavy industries, and distribution systems. Though ICSs were kept isolated from the Internet for so long, significant achievable business benefits are driving a convergence between ICSs and the Internet as well as information technology (IT) environments, such as cloud computing. As a result, ICSs have been exposed to the attack vectors used in the majority of cyber-attacks. However, ICS devices are inherently much less secure against such advanced attack scenarios. A compromise to ICS can lead to enormous physical damage and danger to human lives. In this work, we have a close look at the shift of the ICS from stand-alone systems to cloud-based environments. Then we discuss the major works, from industry and academia towards the development of the secure ICSs, especially applicability of the machine learning techniques for the ICS cyber-security. The work may help to address the challenges of securing industrial processes, particularly while migrating them to the cloud environments.
راعي المشروعAmerican Association for the Advancement of Science; IEEE Foundation; Qatar Foundation; Qatar National Research Fund; Anacostia Community Museum; Academy of Science of St. Louis
اللغةen
الناشرElsevier Ltd
الموضوعCloud computing
Computation theory
Computer crime
Distributed parameter control systems
Industrial plants
Intrusion detection
Learning systems
Machine learning
Man machine systems
Network security
Programmable logic controllers
SCADA systems
Cyber security
Distribution systems
Industrial control systems
Intrusion Detection Systems
Machine learning techniques
Programmable logic controllers (PLC)
System configurations
Water treatment facilities
Industrial water treatment
العنوانCybersecurity for industrial control systems: A survey
النوعArticle Review
رقم المجلد89
dc.accessType Abstract Only


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