An attention-based LSTM model with XAI detects AI-assisted ransomware at early stages by analyzing file system behavioral sequences.
Automated Dynamic Analysis of Ransomware: Benefits, Limitations and Use for Detection
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TL-RL-FusionNet uses frozen transfer learning backbones and a Q-learning agent to adaptively reweight training samples for ransomware detection, reporting 99.1% accuracy on a 1000-sample dataset.
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Explainable Attention-Based LSTM Framework for Early Detection of AI-Assisted Ransomware via File System Behavioral Analysis
An attention-based LSTM model with XAI detects AI-assisted ransomware at early stages by analyzing file system behavioral sequences.
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TL-RL-FusionNet: An Adaptive and Efficient Reinforcement Learning-Driven Transfer Learning Framework for Detecting Evolving Ransomware Threats
TL-RL-FusionNet uses frozen transfer learning backbones and a Q-learning agent to adaptively reweight training samples for ransomware detection, reporting 99.1% accuracy on a 1000-sample dataset.