DDQN-MLP: An Explainable and Adversarially Robust DRL-Guided Adaptive Learning Framework for Ransomware Detection

Ransomware detection remains challenging because modern variants exhibit diverse, evasive, and partly benign-like behaviors that undermine fixed supervised learning objectives. This study proposes DDQN-MLP, a training-time deep reinforcement learning framework for behavioral ransomware detection usi