Autonomous Network

Autonomous networks aim to create self-managing systems capable of automatically detecting and responding to cybersecurity threats, reducing reliance on human intervention. Current research heavily utilizes reinforcement learning, often employing deep neural networks like those with attention mechanisms, and AutoML frameworks to automate tasks such as feature selection and model optimization. This field is crucial for enhancing the security of increasingly complex networks, particularly in critical infrastructure like industrial control systems and next-generation mobile networks, by improving response times and mitigating the limitations of traditional security approaches. The development of robust and generalizable autonomous defense mechanisms remains a key challenge.