Web Application Firewall

Web Application Firewalls (WAFs) are crucial for protecting web applications from attacks by analyzing HTTP traffic and blocking malicious requests. Current research focuses on improving WAF effectiveness through machine learning, employing techniques like One-Class SVMs, and adapting rule-based systems (e.g., ModSecurity) with models that learn to weight rules based on application-specific needs and to better detect adversarial attacks. These advancements aim to reduce false positives and improve the detection of sophisticated attacks, ultimately enhancing web application security and contributing to more robust cybersecurity defenses.