Automated Generative AI-Driven Forensic Analysis (AGAFA). An Explainable Neuro-Symbolic Approach to Digital Forensics

Abstract

Digital Forensics (DF) encompasses the processes of collecting, analysing, and preserving digital evidence crucial for investigations involving cybercrime, security breaches and other criminal cases. The rising number of digital devices requiring investigation, coupled with diminishing confidence in the legal process due to the extensive time needed to process these devices, has prompted the development of a novel framework known as AGAFA. This framework, powered by Explainable AI, aims to meet the growing demand for digital forensic services. The primary objectives of this hybrid neuro-symbolic approach are to enhance the transparency of Artificial Intelligence (AI) in forensic analyses and to protect digital systems. Additionally, it leverages the capabilities of Large Language Models (LLMs) to extract insights from vast datasets in a timely and cost-effective manner. A potential use case for this framework is also illustrated, showcasing its practical application.