Deepfake and Image Forgery Detection: Cybersecurity, Multimedia Forensics, Image Manipulation (De Gruyter STEM)

Deepfake and image forgery technologies have advanced at an alarming rate, creating significant challenges for digital forensics and cybersecurity professionals. Beyond technical concerns, the abuse of these technologies poses profound societal risks, including erosion of trust, reputational harm, and the exploitation of vulnerable populations, such as through image-based abuse and social engineering attacks.

This book provides a comprehensive exploration of tools, techniques, and workflows for authenticating digital imagery. Topics include AI-based feature extraction, forensic analysis of metadata, lighting, and textures, and detecting temporal inconsistencies in videos. Each chapter equips forensic analysts, IT professionals, and law enforcement personnel with actionable insights, case studies, and reliable methods for detecting manipulation while addressing ethical and legal considerations.

This book is an essential resource for practitioners and researchers seeking to mitigate the social and legal consequences of forgery abuse and ensure the integrity of digital evidence in an increasingly complex technological landscape.

Dr. Chad R. Johnson is a computer criminologist and cybersecurity expert with years of experience in the field. He serves as a professor in the Department of Computing and New Media Technologies at the University of Wisconsin–Stevens Point, where he directs both the Digital Forensics and Recovery Analysis Lab (DFRAL) and the Center for Cybersecurity Studies and Advanced Research (CCSAR). With a PhD in Cyber Defense from Dakota State University and a Master's in Criminal Justice Theory from UW–Platteville, Dr. Johnson has built his career on advancing methods of multimedia evidence analysis, image forgery detection, computer investigations, and cyber-intelligence.