Generative AI for Cyber Threat Simulation and Defense

Generative AI enhances cybersecurity by simulating various cyber threats and strengthening possible defense mechanisms. The paper proposes using generative adversarial networks and variational auto-encoders for cyber threat simulation and defense. The main contributions include new methodologies to simulate realistic cyber-attacks and develop robust defense strategies. Experimental results show that generative AI can hugely improve threat detection and response time compared to traditional methods. The results underline the vast potential for generative AI to transform cybersecurity practice and lay the foundations for a much more resilient and adaptive security framework.