Research on intelligent adversarial attack and defense based on GAN and RL

This article aims to explore the research progress of intelligent adversarial attack and defense strategies based on Generative Adversarial Networks (GANs) and Reinforcement Learning (RL). By combining these two advanced technologies, this article analyzes the mechanism of adversarial sample generation and its potential threats in real-world applications. At the same time, a series of targeted defense measures have been proposed to enhance the robustness of the system in the face of intelligent attacks. The research results indicate that the combination of GAN and RL provides a new perspective and solution for improving network security.