The increasing sophistication of anti-forensic techniques, including steganography, encryption and metadata manipulation presents a formidable challenge to traditional digital forensic tools. This research investigates the limitations of widely adopted forensic platforms- FTK Imager, Autopsy and Volatility-in detecting and analyzing such evasive tactics. Through controlled experimental evaluation, the study is assessed across simulated anti-forensic scenarios, revealing critical performance gaps in detection accuracy and evidence recovery. To address these deficiencies, a conceptual framework integrating artificial(AI) and blockchain technology is proposed.
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