2026
DRMD: Deep Reinforcement Learning for Malware Detection Under Concept Drift
AAAI 2026technical
Malware detection in real-world settings must deal with evolving threats, limited labeling budgets, and uncertain predictions. Traditional classifiers, without additional mechanisms, struggle to maintain performance under concept drift in malware domains, as their supervised learning formulation can