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  <doi_batch_id>aspg-37-2330-1792223505</doi_batch_id>
  <timestamp>20261017075145</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <journal>
   <journal_metadata language="en">
    <full_title>Financial Technology and Innovation</full_title>
    <abbrev_title>FinTechI</abbrev_title>
    <issn media_type="electronic">2836-5372</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2023</year>
    </publication_date>
    <journal_volume>
     <volume>3</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Ensuring Brand Safety and Reputation in Digital Marketing with Advanced Cybersecurity Protocols</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Ashish</given_name>
      <surname>Raghuwanshi</surname>
      <affiliations>
       <institution>
        <institution_name>Department of Electronics &amp;. Communication Engineering, IES College of Technology, Bhopal, Madhya Pradesh, India</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>The ever-changing world of digital marketing makes it more important than ever to protect the integrity of brands. This study presents a novel method called &quot;Enhanced Brand Safety Assurance through Cybersecurity Protocols&quot; that combines three important algorithms: Ad Fraud Detection and Prevention, Real-time Behavioral Analysis, and Threat Intelligence Integration. The security of digital advertising, privacy of sensitive information, and customer confidence may all be assured with this framework's proactive threat detection and mitigation capabilities. A strong protection system against ever-changing cyber threats is created by combining the unique characteristics of each algorithm. To react to the constantly changing cybersecurity scene, the suggested solution uses adaptive thresholds, machine learning, and sophisticated analytics. When compared to more conventional approaches, the suggested solution outperforms them in terms of important efficacy indicators and practical implementation details. Experiments show that it can learn a lot, integrate AI, adapt to threats, monitor in real-time, and identify threats very well. Brands can protect themselves from the complex digital threat environment with this comprehensive and proactive cybersecurity solution that tackles the many problems associated with digital marketing.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2023</year>
    </publication_date>
    <pages>
     <first_page>08</first_page>
     <last_page>17</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">2330</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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    <doi_data>
     <doi>10.54216/FinTech-I.030101</doi>
     <resource>https://americaspg.com/journal/37/article/2330</resource>
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