A Gradient-Optimized TSK Fuzzy Framework for Explainable Phishing Detection
A gradient-optimized fuzzy logic framework for phishing detection prioritizes explainability over black-box accuracy, aligning with growing EU AI Act demands for transparent security tooling.
Summary written by editorial AI · Source link below
arXiv:2504.18636v2 Announce Type: replace Abstract: Phishing attacks represent an increasingly sophisticated and pervasive threat to individuals and organizations, causing significant financial losses, identity theft, and severe damage to institutional reputations. Existing phishing detection methods often struggle to simultaneously achieve high accuracy and explainability, either failing to detect novel attacks or operating as opaque black-box models. To address this critical gap, we propose a
Editorial Analysis
As the EU AI Act pushes for explainability in high-risk AI systems, security tools that offer interpretable decisions gain a regulatory edge over opaque alternatives.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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