PHISHGUARD: A Hybrid GCN-BERT Framework for Context- Aware Social Media Phishing Detection Aligned with MITRE ATT&CK

Authors

  • Karpurapu Rajesh
  • Sagar Imambi

Keywords:

social media phishing

Abstract

Social media phishing attacks have increased by 72 % globally since 2023, driven by AI-generated lures
and coordinated cross-platform campaigns. Traditional detectors based solely on natural language processing or static
rules suffer from high false positives and delayed responses.

Downloads

Published

2025-07-17

How to Cite

Karpurapu Rajesh, & Sagar Imambi. (2025). PHISHGUARD: A Hybrid GCN-BERT Framework for Context- Aware Social Media Phishing Detection Aligned with MITRE ATT&CK. Utilitas Mathematica, 122(1), 2172–2178. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/2477

Citation Check

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.