February 24, 2020 Conference paper Open Access

Igor Kotsiuba; Inna Skarga-Bandurova; Alkiviadis Giannakoulias; Mykhailo Chaikin; Aleksandar Jevremovic

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    <subfield code="u">School of Engineering, Computing and  Mathematics   Oxford Brookes University   Oxford, United Kingdom</subfield>
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    <subfield code="a">Inna Skarga-Bandurova</subfield>
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    <subfield code="u">School of Electrical and Computing  Engineering   National Technical University of  Athens  Athens, Greece</subfield>
    <subfield code="a">Alkiviadis Giannakoulias</subfield>
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    <subfield code="u">CRDF Global, Kyiv, Ukraine</subfield>
    <subfield code="a">Mykhailo Chaikin</subfield>
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    <subfield code="u">IEEE member, Serbia</subfield>
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    <subfield code="u">https://zenodo.org/record/3891124/files/[13] Technique for Finding and Investigating the Strongest Combinations of Cyberattacks on Smart Grid Infrastructure.pdf</subfield>
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    <subfield code="u">G.E. Pukhov Institute for Modeling in  Energy Engineering, National Academy  of Sciences of Ukraine  Kyiv, Ukraine</subfield>
    <subfield code="a">Igor Kotsiuba</subfield>
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    <subfield code="a">Technique for Finding and Investigating the  Strongest Combinations of Cyberattacks on Smart  Grid Infrastructure</subfield>
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    <subfield code="a">SPEAR: Secure and PrivatE smArt gRid</subfield>
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    <subfield code="a">&lt;p&gt;Recently, smart grids have become a vector of&amp;nbsp;the energy policy of many countries. Due to structural and&amp;nbsp;operation features, smart grids are a constant target of&amp;nbsp;combined and simultaneous cyberattacks. To maximize security&amp;nbsp;and to optimize existing network schemes to prevent cyber&amp;nbsp;intrusion, in this paper, we propose an approach to decision&amp;nbsp;support in finding and identifying the most potent attack&amp;nbsp;combinations that can set the system to maximum damage. The&amp;nbsp;main purpose is to identify the most severe combinations of attacks on smart grid components that potentially can be&amp;nbsp;implemented from the perspective of the attacker. In this&amp;nbsp;context, the problem of finding weaknesses points in the&amp;nbsp;network configuration of a smart grid and assessing the impact&amp;nbsp;of events on cyberinfrastructure is considered. The technique&amp;nbsp;for detecting and investigating the strongest combinations of&amp;nbsp;cyberattacks on the smart grid network is given with an&amp;nbsp;example of the analysis of the spread of pandemic software in a&amp;nbsp;system with arbitrary structure.&amp;nbsp;&lt;/p&gt;</subfield>
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    <subfield code="a">10.1109/bigdata47090.2019.9006335</subfield>
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