MininetGym: A modular SDN-based simulation environment for reinforcement learning in cybersecurity

Salvo Finistrella, Stefano Mariani, Franco Zambonelli

Abstract: Highlights•A modular simulator for Reinforcement Learning (RL) in Software Defined Network-based network scenarios.•Supports both tabular (Q-learning, SARSA) and deep RL (DQN, PPO, A2C) agents.•Real-time traffic generation and flow monitoring via Mininet and OpenDaylight.•Custom Gym environments for traffic classification and Denial of Service attack detection.•Configurable setup for benchmarking RL models in cybersecurity experiments.