Artificial Intelligence Driven Forensics

Introduction

This book explores the transformative role of artificial intelligence (AI) in the field of digital forensics, offering a comprehensive overview of how AI technologies are reshaping crime investigation, cybersecurity, and evidence analysis.

Methodologies

The book bridges traditional forensic methodologies with cutting-edge AI techniques, such as machine learning, deep learning, natural language processing, and graph analytics, to improve the accuracy, speed, and scalability of forensic investigations.

Applications and Case Studies

Structured around real-world applications and case studies, the book covers critical areas including AI-enhanced malware detection, user behavior profiling, deep fake identification, social media profile cloning detection, canine forensics and hybrid approaches to analyzing digital artifacts.

Integration with Forensic Tools

It also delves into the integration of AI with forensic tools for automating incident response, identifying anomalies in massive log files, and supporting decision-making in complex cybercrime scenarios.

Interdisciplinary Approach

A key feature of the book is its interdisciplinary approach, blending insights from computer science, cybersecurity, law, and ethics. It addresses not only the technical mechanisms behind AI-driven forensics but also the legal, ethical, and societal implications, particularly regarding privacy, accountability, and the admissibility of AI-generated evidence in courts.

Target Audience

Geared toward researchers, practitioners, students, and policymakers, Artificial Intelligence Driven Forensics serves as both a foundational text and an advanced guide to understanding the future of forensic science in the age of AI.