AI-Controlled Botnets And Ai-Based Ddos Attack Detection

Abstract

Artificial intelligence (AI) is transforming cybersecurity by influencing both offensive and defensive tactics. AI-powered botnets use automated decision-making to evade detection and launch sophisticated attacks, while AI-based defense systems rely on machine learning to identify and respond to Distributed Denial-of-Service (DDoS) threats in real time. This paper summarizes six major studies showcasing advances in AI-driven botnets and AIenhanced DDoS detection, particularly suited to Java-based environments. Key challenges such as adversarial tactics, false positives, and resource constraints are examined. A comparative review of various DDoS attack types and related AI detection methods is also provided, highlighting both the strengths and the limitations of current solutions.