arXiv Machine Learning
CyberHull: Deterministic Malicious URL Isolation via Convex Hull
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arXiv Machine Learning
Jun 2
A Lightweight Hybrid MLP-Based Framework for Real-Time Phishing URL Detection Using Structural URL Features
arXiv:2606. 00889v1 Announce Type: cross Abstract: Phishing attacks remain a major cybersecurity threat, exploiting deceptive URLs to steal sensitive user information.
arXiv AI
Sep 24
Comparative Evaluation of Static Embedding Models for HTTP Request Anomaly Detection
The paper benchmarks static embedding models—Word2Vec, FastText, and Doc2Vec—for detecting anomalous HTTP requests using a single‑class classification framework. It introduces HEDA, a modular pipeline that trains both embeddings and detectors solely on benign traffic in an unsupervised setting. Experiments on synthetic and real datasets show that FastText embeddings consistently yield high detection rates with controlled false positives.
arXiv AI
Aug 18
A Tree-Structured Approach for Phishing Template and Attacker Attribution Analysis
arXiv:2608. 16158v1 Announce Type: cross Abstract: Phishing remains a persistent and evolving cybersecurity threat, with attack volumes reaching record levels.
arXiv AI
Jun 6
Dimensionality Reduction for Cyberattack Classification: A Comparative Evaluation of PCA and Linear Predictive Coding
arXiv:2606. 05584v1 Announce Type: cross Abstract: High-dimensional feature representations are widely used in machine learning-based cyberattack detection systems.
arXiv Machine Learning
Jun 24
A Hybrid, Multi-Layered Pipeline for Phishing and Threat Classification: Independently Validated URL and NLP Engines with a Calibrated Multi-Channel Fusion Stage
arXiv:2606. 21690v2 Announce Type: replace-cross Abstract: Phishing is a multi-modal threat.
arXiv AI
Aug 18
Breaking and Defending LLM-Powered Social Media Bot Detection Systems
arXiv:2608. 15893v1 Announce Type: new Abstract: The rise of social media bots poses a persistent threat, enabling misinformation, opinion manipulation, and the erosion of trust in online platforms.