Adversarial Reinforcement Learning for Offensive and Defensive Agents in a Simulated Zero-Sum Network Environment

Abrar Shahid, Ibteeker Mahir Ishum, AKM Tahmidul Haque +2

This paper presents a controlled study of adversarial reinforcement learning in network security through a custom OpenAI Gym environment that models brute-force attacks and reactiv…