A Graph-Attentive LSTM Model for Malicious URL Detection

Malicious URLs pose significant security risks as they facilitate phishing attacks, distribute malware, and empower attackers to deface websites. Blacklist detection methods fail to identify new or obfuscated URLs because they depend on pre-existing patterns. This work presents a hybrid deep...

URL2Graph++: Unified Semantic-Structural-Character Learning for Malicious URL Detection

Malicious URL detection remains a major challenge in cybersecurity, primarily due to two factors: 1 the exponential growth of the Internet has led to an immense diversity of URLs, making generalized detection increasingly difficult; and 2 attackers are increasingly employing sophisticated...