Enhancing Cloud Security Against DDoS Attacks: A Comprehensive Review of ML and DL-Based Defence Mechanisms
Rachna Singh, Nitasha Soni · 2024
Cloud computing revolutionized the management of IT infrastructure for organizations, but it also introduced new security hurdles, particularly in countering DDoS attacks. In response, Machine Learning and Deep Learning techniques emerged as promising strategies to bolster cloud security by enhancing DDoS attack detection and mitigation capabilities. This in-depth review examined the implementation of ML and DL-based defense mechanisms aimed at safeguarding cloud environments against DDoS attacks. It scrutinized various ML and DL algorithms, along with their deployment architectures, assessing their efficacy in identifying and mitigating DDoS threats. By synthesizing existing literature and empirical studies, this review provided insights into past advancements, challenges encountered, and future pathways in leveraging ML and DL to fortify cloud security against DDoS attacks.