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<article article-type="research-article" dtd-version="1.3" xml:lang="en">
  <front xmlns:xlink="http://www.w3.org/1999/xlink">
    <journal-meta>
      <journal-id journal-id-type="elibrary">9004</journal-id>
      <journal-title-group>
        <journal-title>Problems of information security. Computer systems</journal-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Проблемы информационной безопасности. Компьютерные системы</trans-title>
        </trans-title-group>
      </journal-title-group>
      <issn pub-type="epub">2071-8217</issn>
    </journal-meta>
    <article-meta xmlns:xlink="http://www.w3.org/1999/xlink">
      <article-id pub-id-type="publisher-id">2</article-id>
      <title-group>
        <article-title>Anomaly detection in cyber-physical systems using graph neural networks</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Обнаружение атак в сетях с динамической топологией на основе адаптивной нейро-нечеткой системы вывода</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Ivanov</surname>
            <given-names>M.</given-names>
          </name>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-1345-1874</contrib-id>
          <name>
            <surname>Pavlenko</surname>
            <given-names>Evgeny</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>pavlenko_eyu@spbstu.ru</email>
        </contrib>
      </contrib-group>
      <aff id="aff1">Peter the Great St. Petersburg Polytechnic University</aff>
      <pub-date publication-format="electronic" date-type="pub" iso-8601-date="2021-06-03">
        <day>03</day>
        <month>06</month>
        <year>2021</year>
      </pub-date>
      <issue>2</issue>
      <fpage>21</fpage>
      <lpage>40</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://jisp.spbstu.ru/userfiles/files/soderzhaniya/2021_2-7-8.pdf"/>
      <abstract xml:lang="en">
        <p>This paper presents a security study of networks with dynamic topology. As a solution to the problem of attack detection, an approach to attack detection in networks with dynamic topology based on adaptive neuro-fuzzy inference system was developed. A software layout of the system that implements the proposed approach has been developed and its effectiveness has been evaluated using various metrics. Experimental results confirmed the validity and effectiveness of the developed approach for attack detection in networks with dynamic topology</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>dynamic topology networks</kwd>
        <kwd>attack detection</kwd>
        <kwd>network security</kwd>
        <kwd>machine learning</kwd>
        <kwd>fuzzy logic</kwd>
        <kwd>neural networks</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
