International Journal of Research and Innovation in Applied Science (IJRIAS)
Hybrid AI Models for Detecting and Preventing Phishing Email
Published May 19, 2026 • Vol. 11, Issue 4, pp. 2449–2453Open Access
DOI: 10.51584/IJRIAS.2026.110400184
Abstract
As cybercriminals adopt advanced AI to launch "PhishBots"—automated tools that create highly realistic and personalized scam emails—traditional "black-box" security measures are failing to maintain user trust (Kumarage et al., 2025; Roy et al., 2023; Uddin & Sarker, 2024). This paper introduces a transparent, hybrid framework that combines the deep-learning power of RoBERTa-base with the SHAP interpretability engine. Our model achieves a peak accuracy of 99.43% on the PhreshPhish benchmark (Dalton et al., 2025; Meléndez et al., 2024).
By optimizing input sequences to 128 tokens, we achieve sub-100ms inference times, making it suitable for real-time enterprise deployment (Ferrag et al., 2023; Shirazi et al., 2022). This approach provides a "Digital Highlighter" for security analysts, transforming automated alerts into verifiable forensic evidence (Al‐Fayoumi et al., 2024; Lim et al., 2025).
Keywords: Explainable AI, Phishing Detection, RoBERTa, SHAP, Cybersecurity, Digital Forensics, Data Privacy.
| Journal | International Journal of Research and Innovation in Applied Science (IJRIAS) |
|---|---|
| ISSN | 2454-6194 |
| Volume / Issue | Volume 11, Issue 4 |
| Pages | 2449–2453 |
| Publication date | May 19, 2026 |
| DOI | 10.51584/IJRIAS.2026.110400184 |
| Publisher | RSIS International |
| License | Open Access |
How to cite this article
Ritaben Meghajibhai Marawada, & prof Nilesh Modi (2026). Hybrid AI Models for Detecting and Preventing Phishing Email. International Journal of Research and Innovation in Applied Science (IJRIAS), 11(4), 2449-2453. https://doi.org/10.51584/IJRIAS.2026.110400184
BibTeX
@article{Ritaben2026,
title = {Hybrid AI Models for Detecting and Preventing Phishing Email},
author = {Ritaben Meghajibhai Marawada and prof Nilesh Modi},
journal = {International Journal of Research and Innovation in Applied Science (IJRIAS)},
volume = {11},
number = {4},
pages = {2449--2453},
year = {2026},
doi = {10.51584/IJRIAS.2026.110400184},
publisher = {RSIS International}
}