Embedding a 4:1 false-negative-to-false-positive penalty ratio into DRL reward signals reduces missed ransomware detections by 43% relative to symmetric rewards across 480 controlled runs.
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SA-DRL: Security-Aware Deep Reinforcement Learning for Ransomware Detection with Asymmetric Reward Design
Embedding a 4:1 false-negative-to-false-positive penalty ratio into DRL reward signals reduces missed ransomware detections by 43% relative to symmetric rewards across 480 controlled runs.