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<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Journal of Management and Business Solutions</JournalTitle>
      <Issn>3092-7226</Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2027</Year>
        <Month>07</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>An Integrated Cybersecurity Audit Model for Intelligent Systems with Emphasis on Risk Assessment and Digital Resilience</ArticleTitle>
    <VernacularTitle>An Integrated Cybersecurity Audit Model for Intelligent Systems with Emphasis on Risk Assessment and Digital Resilience</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>16</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2026</Year>
        <Month>02</Month>
        <Day>10</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;The present study aimed to develop an integrated cybersecurity auditing model for intelligent systems with an emphasis on risk assessment and digital resilience within contemporary digital and AI-driven organizational environments. This study was conducted using a qualitative exploratory approach based on grounded theory-oriented analysis. The statistical population consisted of experts in internal auditing, cybersecurity, information technology risk management, chief information officers (CIOs), members of audit committees, and university professors specializing in intelligent systems and cybersecurity governance in Tehran. Participants were selected through purposive and snowball sampling methods, and data collection continued until theoretical saturation was achieved. In total, 23 in-depth semi-structured interviews were conducted. The collected data were transcribed and analyzed using MAXQDA software through open, axial, and selective coding procedures. To ensure the trustworthiness of the findings, member checking, peer review, and continuous comparison techniques were utilized throughout the analytical process. The findings revealed that cybersecurity auditing in intelligent systems is a multidimensional and adaptive governance process integrating technological, organizational, behavioral, operational, and resilience-oriented dimensions. The open coding stage identified major concepts including intelligent infrastructure vulnerabilities, cyber risk governance, AI assurance, digital resilience capabilities, continuous monitoring systems, incident response management, and human-centered cybersecurity controls. Axial coding demonstrated that these dimensions are interconnected through strategic governance mechanisms, predictive risk assessment processes, and resilience-oriented auditing structures. Selective coding ultimately led to the development of a comprehensive integrated cybersecurity auditing model in which digital resilience functioned as the central organizing principle connecting continuous monitoring, intelligent risk management, governance accountability, and adaptive operational response capabilities. The results indicated that traditional cybersecurity auditing frameworks are insufficient for addressing the complexity of intelligent digital ecosystems and AI-driven infrastructures. Organizations require integrated and resilience-oriented cybersecurity auditing models capable of combining continuous monitoring, strategic governance, intelligent threat analysis, AI assurance, and adaptive risk management. The proposed model provides a comprehensive framework for strengthening organizational digital resilience, improving cybersecurity governance effectiveness, and enhancing preparedness against emerging cyber threats in intelligent systems environments.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Cybersecurity Auditing</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Intelligent Systems</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Digital Resilience</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Risk Assessment</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Artificial Intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Cyber Governance</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Continuous Monitoring</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Intelligent Infrastructure</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Cyber Risk Management</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Adaptive Security Systems</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalmbs.com/index.php/jmbs/article/download/321/278</ArchiveCopySource>
  </Article>
</ArticleSet>
