CyberHull: Deterministic Malicious URL Isolation via Convex Hull
The emergence of increasingly sophisticated and evasion-resistant phishing attack strategies represents a significant threat to modern cybersecurity, particularly in cyber-physical systems and internet-based networks. Traditional probabilistic methods and certain machine learning approaches often struggle to detect novel attacks and may lack interpretability or portability. To address these challenges, we introduce CyberHull, a resource-efficient and deterministic framework for identifying malicious URLs through mathematically defined convex hull boundaries across multiple orthogonal feature domains, including structural content entropy, hyperlink graph topology, and semantic token distri...
| Authors | Avijit Gayen, Aniket Ghosal, Durba Chakraborty et al. |
|---|---|
| Primary category | cs.CR |
| Published | 20 October 2026 |
| Last updated at source | 20 October 2026 |
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