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      Intrusion Detection via Machine Learning for SCADA System Protection

      proceedings-article
      ,
      1st International Symposium for ICS & SCADA Cyber Security Research 2013 (ICS-CSR 2013) (ICSCSR)
      ICS & SCADA Cyber Security Research 2013
      16-17 September 2013
      Machine learning, SCADA systems, Infrastructure protection
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            Abstract

            SCADA (Supervisory Control And Data Acquisition) systems have always been susceptible to cyber-attacks. Different types of cyber-attacks could occur depending on the architecture and configurations used in the SCADA system. To protect cyber infrastructure from above attacks a growing collaborative effort between cyber security professionals and researchers from private and academia has involved in designing variety of intelligent intrusion detection systems. This paper introduces a new European Framework-7 project CockpitCI and roles of intelligent machine learning methods to prevent SCADA systems from cyber-attacks.

            Content

            Author and article information

            Contributors
            Conference
            September 2013
            September 2013
            : 101-105
            Affiliations
            [0001]Department of Computing, University of Surrey

            Guildford, GU2 7XH, UK
            Article
            10.14236/ewic/ICSCSR2013.12
            15689009-1bf1-4c85-84ea-09879dd38069
            © S.L.P. Yasakethu et al. Published by BCS Learning and Development Ltd. 1st International Symposium for ICS & SCADA Cyber Security Research 2013 (ICS-CSR 2013), Leicester, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            1st International Symposium for ICS & SCADA Cyber Security Research 2013 (ICS-CSR 2013)
            ICSCSR
            1
            Leicester, UK
            16-17 September 2013
            Electronic Workshops in Computing (eWiC)
            ICS & SCADA Cyber Security Research 2013
            Product
            Product Information: 1477-9358BCS Learning & Development
            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/ICSCSR2013.12
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            Machine learning,SCADA systems,Infrastructure protection

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