Advancements in Ransomware Detection Using NVMe Streams
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🛡️✨ Innovative Language Modeling Techniques Enhance Ransomware Detection in NVMe Streams. Researchers have developed two transformer-based models, the Command-Level Transformer (CLT) and the Patch-Level Transformer (PLT), to improve ransomware detection in NVMe command sequences. The CLT focuses on classifying individual commands to identify ransomware activity, while the PLT estimates the data volume accessed by ransomware within command patches. These models demonstrate significant advancements over traditional tabular methods, achieving up to a 24% reduction in missed detections, a 66% improvement in data loss prevention, and an 84% increase in accurately identifying data accessed by ransomware. This research represents a promising step forward in cybersecurity measures against ransomware threats.
