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Editorial

Enhancing Spear Phishing Defense with AI: A Comprehensive Review and Future Directions

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  • @ARTICLE{10.4108/eetsis.6109,
        author={Nachaat Mohamed and Hamed Taherdoost and Mitra Madanchian},
        title={Enhancing Spear Phishing Defense with AI: A Comprehensive Review and Future Directions},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={12},
        number={1},
        publisher={EAI},
        journal_a={SIS},
        year={2025},
        month={4},
        keywords={Artificial Intelligence, Spear Phishing, Cybersecurity, Email Threat Detection, Machine Learning, Natural Language Processing},
        doi={10.4108/eetsis.6109}
    }
    
  • Nachaat Mohamed
    Hamed Taherdoost
    Mitra Madanchian
    Year: 2025
    Enhancing Spear Phishing Defense with AI: A Comprehensive Review and Future Directions
    SIS
    EAI
    DOI: 10.4108/eetsis.6109
Nachaat Mohamed1,*, Hamed Taherdoost2, Mitra Madanchian2
  • 1: Rabdan Academy
  • 2: University Canada West
*Contact email: eng.cne9@gmail.com

Abstract

This paper presents a critical analysis of the role of Artificial Intelligence (AI) in defending against spear phishing attacks, which continue to be a significant cybersecurity threat. By examining 30 seminal studies, we provide an in-depth evaluation of current AI techniques, such as machine learning, natural language processing, and behavioural analytics, which are utilized to detect and mitigate sophisticated email threats. Our review uncovers that AI not only significantly enhances the detection capabilities against these tar-geted attacks but also faces challenges like adaptability and false positives. These findings highlight the continuous evolution of AI strategies in spear phishing defense and the need for ongoing innovation to keep pace with ad-vanced threat tactics. This paper aims to guide future research by proposing integrated AI solutions that enhance both detection capabilities and respon-siveness to new threats, thereby strengthening cybersecurity defenses in an increasingly digital world.

Keywords
Artificial Intelligence, Spear Phishing, Cybersecurity, Email Threat Detection, Machine Learning, Natural Language Processing
Received
2025-04-11
Accepted
2025-04-11
Published
2025-04-11
Publisher
EAI
http://dx.doi.org/10.4108/eetsis.6109

Copyright © 2024 N. Mohamed et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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