Command & Control (C2) Traffic Detection Via Algorithm Generated Domain (Dga) Classification Using Deep Learning And Natural Language Processing

arXiv — cs.LG•Wednesday, December 10, 2025 at 5:00:00 AM

PositiveArtificial Intelligence

A recent study has introduced a method for detecting Command and Control (C2) traffic through the classification of Domain Generation Algorithms (DGA) using Deep Learning and Natural Language Processing (NLP). The research involved a hybrid database of 100,000 domains, achieving a detection accuracy of 97.2% with a reduced false positive rate.
This advancement is significant as it addresses the limitations of traditional blacklist-based defenses against sophisticated malware that utilizes dynamic domain generation, enhancing cybersecurity measures.
The integration of advanced machine learning techniques, such as Deep Learning, is becoming increasingly vital in various fields, including cybersecurity and medical diagnostics. The ability to detect complex patterns in data not only improves security protocols but also reflects a broader trend of leveraging AI for enhanced decision-making and efficiency across multiple domains.

— via World Pulse Now AI Editorial System

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