Abstract

The rapid expansion of future communication networks, including 5G, beyond 5G, Internet of Things (IoT), and software-defined infrastructures, has significantly increased exposure to sophisticated cyber threats. Traditional security mechanisms, which rely heavily on static rules and human intervention, are no longer sufficient to counter highly dynamic, large-scale, and automated cyber-attacks. This paper presents an autonomous cyber threat response model designed for future communication networks, leveraging artificial intelligence and autonomous control mechanisms to detect, analyze, and mitigate cyber threats in real time. The proposed model integrates machine learning-based threat intelligence, adaptive decision-making, and closed-loop control systems to enable rapid and coordinated responses without manual oversight. By continuously learning from network behavior and threat patterns, the system dynamically adjusts its defense strategies to maintain network integrity, availability, and confidentiality. The study emphasizes resilience, scalability, and adaptability as essential properties of autonomous cyber defense systems. Experimental analysis demonstrates that autonomous response models can significantly reduce detection latency, minimize attack impact, and improve overall network security posture. This research highlights the necessity of autonomous cyber threat response as a foundational capability for securing future communication infrastructures