Date of Publication : April 2026

Abstract: Investigating large volumes of digital evidence from forensic reports such as Unified Forensic Data Reports (UFDR) is often time-consuming and complex when performed manually. This study proposes an AI-Powered Digital Forensics Assistant that leverages Artificial Intelligence (AI) and Natural Language Processing (NLP) to simplify and accelerate digital investigations. The system automatically processes forensic datasets to extract key information including messages, call logs, contacts, and media files. It supports multilingual detection and translation, enabling investigators to analyze diverse communication data efficiently. Additionally, users can perform natural language queries such as identifying conversations related to financial or suspicious activities. The system detects patterns, keywords, and behavioral trends to highlight potential evidence. An interactive visualization module presents communication networks, timelines, and activity graphs, providing clear and actionable insights. By integrating AI-driven automation with traditional forensic methods, the proposed system significantly enhances the efficiency and accuracy of digital investigations, reducing manual effort and enabling faster evidence discovery.

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