Mitigating DDoS Attacks in Cloud-Based Systems with Real-Time Detection Algorithms

The research proposes an algorithm which performs real-time detection of Distributed Denial of Service attacks in cloud-based systems. The method implements an anomaly and signature-based detection combination to achieve precision detection along with lower occurrences of false alarms. Research analysts have trained an artificial intelligence model with actual traffic patterns from networks to separate between invalid and valid data requests. Experimental studies verify how the proposed system decreases attack impact yet operates with minimal computational strain. The research findings help in establishing effective real-time DDoS protection methods for cloud security.