Abduraimov Firdavsiy Alisher o'g'li

AN ADAPTIVE HYBRID DEEP LEARNING FRAMEWORK FOR REAL-TIME CYBER THREAT AND ANOMALY DETECTION IN HIGH-THROUGHPUT NETWORK TRAFFIC

Modern enterprise digital infrastructures face unprecedented cyber threats characterized by high volume, zero-day vulnerabilities, and multi-stage attack vectors. Traditional rule-based Intrusion Detection Systems (IDS) and shallow machine learning models struggle to maintain high detection accuracy while minimizing fa...