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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xml:lang="ru">
  <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">4</article-id>
      <title-group>
        <article-title>Fake posts detection using graph neural networks</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Обнаружение фейковых постов с использованием графовых нейронных сетей</trans-title>
        </trans-title-group>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-3102-5950</contrib-id>
          <name>
            <surname>Izotova</surname>
            <given-names>Oksana</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>izotova@ibks.spbstu.ru</email>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0003-2849-4682</contrib-id>
          <name>
            <surname>Lavrova</surname>
            <given-names>Daria</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <email>lavrova_ds@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="2021-11-12">
        <day>12</day>
        <month>11</month>
        <year>2021</year>
      </pub-date>
      <issue>3</issue>
      <fpage>34</fpage>
      <lpage>43</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://jisp.spbstu.ru/userfiles/files/2021_3_5-6.pdf"/>
      <abstract xml:lang="en">
        <p>The paper is devoted to the study of graph neural networks as a separate field and the possibility of their application to solve such an urgent cybersecurity problem as the detection of fake posts. The implementation of a proprietary graph neural network model capable of detecting fake posts is presented, and the results of experimental studies demonstrating the effectiveness of using graph neural networks to solve the problem are presented</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>Information Security</kwd>
        <kwd>Graph Neural Networks</kwd>
        <kwd>Fake Posts</kwd>
        <kwd>Graph Model</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
