Hybrid Supervised Unsupervised Models for DNS Threats
The growing sophistication of cyber threats leveraging DNS as a covert communication and attack vector has driven the need for more advanced detection methods. Traditional signature-based or rule-based approaches are often insufficient against the dynamic, evasive behaviors exhibited by modern attackers. In response, machine learning techniques have become integral to DNS forensics and security. Among…