Multi-Modal Classification of Encrypted
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When Entropy Is Not Enough: Multi-Modal Classification of Encrypted and Compressed Data Fragments
arXiv:2605.31337v1 Announce Type: new Abstract: Reliable identification of encrypted data fragments is essential in cybersecurity, with applications to ransomware detection, digital forensics, and large-scale data analysis. Distinguishing encrypted from compressed fragments is particularly challenging, as short fragments lack structural data and exhibit low statistical redundancy. Traditional statistical methods based on byte-level distributions show limited effectiveness on this task.