AI-Enhanced Digital Forensics: Automated Techniques for Efficient Investigation and Evidence Collection

Abstract

The abstract summarizes AI-enhanced digital forensics topics. It highlights the importance of AI in digital forensic investigations and outlines its major features, historical perspectives, and methodological evolution. The abstract describes how automated methods can streamline evidence collection and investigation. The historical perspective highlights digital forensic procedures from rudimentary file system investigations to AI-driven methods. This progression reflects digital crime's dynamic character and forensic method developments. The AI-enhanced digital forensics methodology includes establishing an effective component model, identifying datasets, gathering data, arranging studies, and considering ethical considerations. Representative datasets and ethical considerations are stressed in the abstract to ensure ethical and responsible AI application in forensic investigations. AI-based systems are evaluated using accuracy, false positive/negative rates, speed and efficiency, scalability, and durability. A straightforward comparison of these parameters across AI algorithms using bar graphs and grouped bar charts helps forensic investigators chooses strategies. In conclusion, AI-enhanced digital forensics is well understood, and performance evaluations, methodological concerns, historical evolution, and ethics are important. AI is being used in digital forensics as technology advances, giving investigators a strong tool to navigate the digital world accurately and efficiently. To use AI responsibly and effectively for justice, technique and ethics must be constantly improved