Transparent and trustworthy CyberSecurity: an XAI-integrated big data framework for phishing attack detection
The proposed approach advances interpretable and scalable CyberSecurity analytics by addressing the gap between predictive accuracy and decision transparency. By integrating Big Data processing with XAI-driven ML, the framework offers a trustworthy solution for real-time threat detection, supporting informed decision-making and regulatory compliance.
Authors
- Muhammad A. B. Fayyaz (ORCID: https://orcid.org/0000-0002-1794-3000)
- Muhammad Hassan (ORCID: https://orcid.org/0000-0002-5713-9658)
- Muhammad Nauman (ORCID: https://orcid.org/0000-0003-3173-2549)
- Hafiz Muhammad Usman Akhtar
- Huseyn Gorbani
Institutions
- Manchester Metropolitan University (GB)
- University of Greater Manchester (GB)
- Queen Mary University of London (GB)
- Islamia University of Bahawalpur (PK)
Publication Details
- Journal
- Frontiers in Big Data
- Published
- 2025-12-18
- DOI
- https://doi.org/10.3389/fdata.2025.1688091
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00