Cyber Defense

Cyber defense research focuses on developing automated and adaptive systems to mitigate increasingly sophisticated cyberattacks. Current efforts leverage machine learning models, including generative adversarial networks (GANs), graph neural networks (GNNs), transformer-based embeddings, and reinforcement learning algorithms, to detect anomalies, predict attacker behavior, and optimize defensive strategies. These advancements aim to improve the speed and effectiveness of threat response, reduce alert fatigue in security operations centers, and enhance overall network resilience against diverse attack vectors, ultimately contributing to stronger cybersecurity for individuals and organizations.

Papers