IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v11y2025i2id1355.html

Human + AI for Enhanced Security: Creating Resilient Systems through Collaboration

Author

Listed:
  • Sudheer Kotilingala

Abstract

The rapidly evolving threat landscape demands a paradigm shift in cybersecurity approaches, moving beyond traditional siloed defenses. This article explores how the integration of human expertise with artificial intelligence creates robust security frameworks capable of addressing sophisticated modern attacks. The complementary nature of these components—with AI excelling at processing speed, pattern recognition, and continuous monitoring, while human analysts provide contextual understanding, ethical judgment, and adaptive reasoning—forms the foundation for resilient security operations. Through practical applications in real-time threat detection, automated incident response, enhanced decision-making, and false positive reduction, organizations can implement comprehensive defense mechanisms that evolve alongside increasingly sophisticated adversaries. Key implementation considerations span both technical requirements and human factors, emphasizing that effective security stems not from choosing between human or artificial intelligence but from thoughtfully integrating both to maximize their complementary strengths.

Suggested Citation

  • Sudheer Kotilingala, 2025. "Human + AI for Enhanced Security: Creating Resilient Systems through Collaboration," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 3079-3089, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1355
    DOI: 10.32628/CSEIT25112780
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112780
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT25112780
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/home/article/download/CSEIT25112780/CSEIT25112780
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT25112780?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1355. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.