Preprint Open access
Comparative Evaluation of Static Embedding Models for HTTP Request Anomaly Detection
Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms. Traditional web application firewalls (WAFs) rely on rule-based approaches that often exhibit high false positive rates and limited adaptability. Recent studies have explored machine learning techniques a …