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  <doi_batch_id>aspg-31-3006-1791687017</doi_batch_id>
  <timestamp>20261011025017</timestamp>
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  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Advances in Applied Computational Intelligence</full_title>
    <abbrev_title>IJAACI</abbrev_title>
    <issn media_type="electronic">2833-5600</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
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    <journal_volume>
     <volume>6</volume>
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    <issue>2</issue>
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    <titles>
     <title>Algorithms for Cybersecurity in CAVs Based On Deep Learning and Their Applications</title>
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    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Sara</given_name>
      <surname>Sawalmeh</surname>
      <affiliations>
       <institution>
        <institution_name>Mutah University, Faculty of Science, Mutah, Jordan</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>This paper is concerned with the study of some novel techniques that using artificial intelligence to protect networks of CAVs from cyberattacks, where we use some machine learning algorithms to detect attacks and compare the machine learning algorithms used for this in terms of accuracy and required operating time. Also, WEKA tool will be used for the desired comparison, as the experiments are carried out on a new dataset, which is a dataset abbreviated from the KDD99 dataset.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>28</first_page>
     <last_page>36</last_page>
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     <item_number item_number_type="article-number">3006</item_number>
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     <doi>10.54216/IJAACI.060203</doi>
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