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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM60412
Volume:
10 |
4 |
April 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Phishing attacks remain one of the most prevalent and dangerous forms of social engineering in cybersecurity. They exploit human error to bypass technological defenses, compromising credentials and sensitive data. This paper presents Capture the Phish, an integrated AI-powered framework that combines transformer-based natural language processing, explainable AI (XAI), and privacy-preserving federated learning. The system transforms phishing detection into an adaptive, interactive learning environment that simultaneously enhances machine intelligence and human awareness. Through deep semantic modeling, contextual explanations, and decentralized model training, the framework provides a scalable, privacy-conscious, and explainable phishing defense system.
KEYWORDS
Publication Date
4/16/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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