AI & DEEP LEARNING-BASED ANOMALY DETECTION FOR DDOS MITIGATION IN MODERN NETWORKS

Distributed Denial of Service (DDoS) attacks pose a significant threat to online systems by overwhelming target servers with illegitimate traffic. Traditional signature-based detection methods struggle with evolving attack patterns. This paper proposes the use of Artificial Intelligence (AI) and deep learning techniques—particularly Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN)—to analyze network traffic and detect anomalous behaviors in real time. The results demonstrate the effectiveness of deep learning models in identifying complex and zero-day DDoS attacks with high accuracy and minimal false positives.