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      Neural Net-Based Anomaly Detection System in Substation Networks

      Published
      proceedings-article
      ,
      6th International Symposium for ICS & SCADA Cyber Security Research 2019 (ICS-CSR)
      Cyber Security Research
      10th-12th September 2019
      Substation, Electric Power Systems, Anomaly Detection, IEC 60870-5-104, IEC 61850, Neural Network
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            Abstract

            Important components of the electric energy distribution systems are primary and secondary substations. Due to the incorporation of legacy communication infrastructure in these systems, they often have inherent cyber-security vulnerabilities. Further, traditional intrusion defence strategies for IT systems are often not applicable. In order to improve cyber-security in substation networks, this paper presents a neural net-based monitoring system. Further, to evaluate the applicability of the system, all experiments were conducted on a real test bed, which represents the substation domain as close as possible to reality. The proposed monitoring system covers several tasks. First, relevant network packets are acquired from network traffic and analysed. Based on these packets statistical features are extracted. Then, classes are defined, and a normal behaviour model of the network is trained by the neural net. New network traffic is compared to the model, in order to determine the nature of the traffic and identify potential anomalies. Finally, the monitoring system is evaluated by conducting several supervised and unsupervised network attacks against the test bed.

            Content

            Author and article information

            Contributors
            Conference
            September 2019
            September 2019
            : 41-48
            Affiliations
            [0001]Limes Security

            Hagenberg, Austria

            www.limessecurity.com
            [0002]University of Applied Sciences

            St. Pölten

            Institute of IT Security Research

            St. Pölten, Austria

            www.fhstp.ac.at
            Article
            10.14236/ewic/icscsr19.6
            502c58ee-ad6a-4827-b7d8-c45eb3f08272
            © Philipp Kreimel et al. Published by BCS Learning and Development Ltd. 6th International Symposium for ICS & SCADA Cyber Security Research 2019

            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/

            6th International Symposium for ICS & SCADA Cyber Security Research 2019
            ICS-CSR
            6
            Athens, Greece
            10th-12th September 2019
            Electronic Workshops in Computing (eWiC)
            Cyber Security Research
            History
            Product

            1477-9358 BCS Learning & Development

            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/icscsr19.6
            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
            Electric Power Systems,Neural Network,IEC 61850,Anomaly Detection,IEC 60870-5-104,Substation

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