Cyber Attack

Cyberattacks pose a significant threat to individuals, organizations, and critical infrastructure, demanding robust detection and mitigation strategies. Current research focuses on developing autonomous defense systems using reinforcement learning and machine learning algorithms, including graph neural networks, transformers, and various classification models (e.g., random forests, support vector machines), to identify anomalies in network traffic, sensor data, and other relevant sources. These advancements aim to improve the accuracy and speed of attack detection, enhance system resilience, and provide explainable insights into attack patterns for more effective response and prevention. The impact of this research is far-reaching, with applications ranging from securing industrial control systems and smart grids to protecting financial institutions and individual users from increasingly sophisticated threats.