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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="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">15</article-id>
      <article-id pub-id-type="doi">10.48612/jisp/p6rt-uvzz-b4k7</article-id>
      <title-group>
        <article-title>Detection of artificially synthesized audio files using graph neural networks</article-title>
        <trans-title-group xml:lang="ru">
          <trans-title>Обнаружение искусственно синтезированных аудиофайлов 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="2024-06-20">
        <day>20</day>
        <month>06</month>
        <year>2024</year>
      </pub-date>
      <issue>2</issue>
      <fpage>169</fpage>
      <lpage>177</lpage>
      <self-uri xmlns:xlink="http://www.w3.org/1999/xlink" content-type="pdf" xlink:href="https://jisp.spbstu.ru/userfiles/files/soderzhaniya/2024_2_eng.pdf"/>
      <abstract xml:lang="en">
        <p>This paper describes a study of the problem of generalizing multimodal data in the detection of artificially synthesized audio files. As a solution to the stated problem, a method is proposed which combines simultaneous analysis of audio file characteristics with its semantic component presented in the form of text. The approach is based on graph neural networks and algorithmic approaches involving the analysis of keywords and text sentiment. The conducted experimental studies confirmed the validity and efficiency of the proposed approach</p>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>deepfake</kwd>
        <kwd>graph neural networks</kwd>
        <kwd>artificially synthesized audio file</kwd>
        <kwd>text analysis</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
