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"File Type Identification – Computational Intelligence for Digital Forensics" utilizes byte-frequency distribution and neural networks to achieve 99.51% accuracy in file classification when metadata is absent. This research, published in the Journal of Digital Forensics, Security and Law , specifically addresses the challenge of identifying altered or missing file extensions. Access the study at ResearchGate .

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