Large Language Models for Email Forensics

Futuristic Pattern Analysis and Approaches
1. Auflage 2026
ISBN: 978-981-5352-26-9
Verlag: Jenny Stanford Publishing

Buch, Englisch, 420 Seiten, Format (B × H): 152 mm x 229 mm

Reihe: Jenny Stanford Series on Fuzzy Theory Frontiers, Volume 3

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.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Dhanaraj, Rajesh Kumar

Sathyamoorthy, Malathy

Poonkuntran, S.

Kumar, S. Aanjan

Kumar Muchahari, Monoj

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit

Inhaltsverzeichnis

1. Introduction to Large Language Model: Fundamentals, Issues and Challenges 2. Introduction to Large Language Models and Their Integration into Digital Forensic in Email Forensics 3. Design of multimodal Large Language Models with transfer learning and computer vision architectural perspective 4. Role of Explainable Large Language Models in Email Forensics: From Decision-Making Perspective 5. Security and privacy concerns of automated e-mail investigation based on LLMs and keyword searching techniques 6. Combining NLP with LLMs to Assess Potential Threats and Email Protection 7. Exploring Open-Source Technologies for E-mail Forensics: A Comprehensive Guide for User Activity and E-mail Traffic Analysis 8. Explainable LLMs for E-mail Forensics: A Catalyst for Trust in E-mail Forensic Analysis 9. Transformative potential and challenges of large language models in email forensics: applications, security, and future directions 10. Role of keyword searching in Large Language Models: Past, Present and Future 11. Text-to-Text Transfer Transformer Email Forensics: A Case Study on MGM Resort Cyber Attack 12. Introduction to Email Forgery: Understanding the Basics and Significance 13. Large Language Model in Email Fraud under the Insurance Sector 14. Case Study: LLM Integration in an E-Commerce Company 15. Design of Multimodal LLMs with Transfer Learning and Computer Vision: An Architectural Perspective 16. Role of Explainable Large Language Models in Email Forensics—From a Decision-Making Perspective

Über Autor(innen)

Rajesh Kumar Dhanaraj is a professor at Symbiosis Institute of Computer Studies and Research, Symbiosis International (Deemed University), India. He holds a PhD from Anna University and has published over 35 research articles. His interests include cyber-physical systems, wireless sensor networks, and cloud computing. He also serves as an expert advisory panel member for Texas Instruments Inc., USA.

Malathy Sathyamoorthy is an associate professor at KPR Institute of Engineering and Technology, India. She holds a PhD from Anna University and has published more than 20 research papers. Her interests include wireless networks, IoT, and machine learning.

S. Poonkuntran is a professor and dean at VIT Bhopal University, India. With over a decade of experience, he has led funded projects from ISRO, DRDO, and MNRE, published over 90 articles, and authored books and patents.

S. Aanjan Kumar holds a PhD in Botnet Security and has over 10 years of academic experience. His research focuses on software engineering, cyber forensics, and network security.

Monoj Kumar Muchahari has over 10 years of experience in academia and industry, with research interests in cloud computing, AI, and machine learning.