Large language models (LLMs) are advanced machine learning models designed to perform Natural Language Processing (NLP) tasks using deep learning on large-scale textual data. Recently, LLMs have gained attention in digital forensics for their ability to enhance investigation efficiency, improve evidence traceability, and support law enforcement activities. Email communication plays a vital role in personal and professional interactions, with a vast number of messages exchanged daily. This volume makes manual inspection time-consuming and increases vulnerability to cyber threats such as phishing, spam, and ransomware. Traditional email forensic methods, which rely on keyword-based searches and predefined rules, often struggle to detect complex and evolving attacks.
This book highlights the role of LLMs as an automated solution for email forensics. By analyzing contextual patterns, linguistic styles, sentiment, and user-specific characteristics, LLMs enable improved identification of legitimate users and detection of suspicious content. These capabilities extend beyond conventional methods, addressing gaps in manual forensic processes and supporting more efficient and intelligent investigation practices.