Autonomous Cybersecurity Framework Using Deep Learning for Threat Prediction, Response, and Self-Healing Systems

Abstract

Now, a new era requires us to develop intelligent, adaptive and autonomous cybersecurity frameworks in place that can predict the threats, respond and recover to all these in real time. In this research, we considered an Autonomous Cybersecurity Framework Using Deep Learning enabling proactive defense mechanisms by integrating several advanced neural architectures such as Convolutional Neural Networks (CNNs), which are commonly used to classify images; Recurrent Neural Networks (RNNs), most popular for building language processing applications; and Deep Reinforcement Learning (DRL). Utilizing behavioral analytics, anomaly detection, and predictive modeling, the proposed system aims to proactively identify Cyber-physical threats prior to being utilized in an attack. Using deep learning, these models can analyze heterogeneous data sources like network traffic and system logs, to accurately identify complex patterns and attacks. In addition, a smart response engine automatically implements mitigation measures such as threat isolation, dynamic policy control and adaptive access rights. The ability of this framework to selfheal is one of its major contributions, which allows the system to recover automatically by way of patching vulnerabilities, reconfiguring systems and utilizing rollback features without any human intervention. This helps to minimize response time, reduces system down-time and improves cyber-resilience. Studies based on experimental insights from recently proposed self-healing systems powered by AI reveal that they can achieve higher detection accuracy and significantly better response efficiency when compared to traditional approaches. It offers a scalable and adaptive approach to securing contemporary distributed threats posed by ever-changing systems found in cloud, IoT, enterprise environments etc., thus marking a significant step forward towards the development of autonomous cybersecurity frameworks.