Advanced Forensic Techniques for Deepfake Detection and Video Integrity Verification

Erscheinungsjahr 2027
ISBN: 978-3-032-45002-9
Verlag: Springer

Buch, Englisch, Format (B × H): 155 mm x 235 mm

Reihe: Information Systems Engineering and Management

This book presents a multidisciplinary examination of contemporary methods for authenticating digital video and detecting manipulated content. This book integrates artificial intelligence, deep learning, digital forensics, cryptographic verification, metadata analysis, compression-artifact examination, and sensor-based authentication to address the increasing difficulty of establishing trust in video evidence. The book covers object-forgery detection using dual-stage CNN–LSTM architectures, video authentication through quantization analysis, metadata and digital-signature verification, and Photo-Response Non-Uniformity-based camera-source examination. This book also presents comparative evaluations of CNN, LSTM, and GRU models and explores ensemble deep learning approaches that incorporate EfficientNet, XceptionNet, Siamese learning, and attention mechanisms for deepfake detection. Experimental evaluations on benchmark datasets and video data from CyberSecurity Malaysia demonstrate the practical strengths and limitations of the proposed approaches. Attention is given to video compression, temporal inconsistencies, subtle manipulation, dataset diversity, generalization, and the computational requirements of real-time detection. By combining theoretical foundations, experimental analysis, and digital-forensic applications, this book provides a valuable reference for researchers, postgraduate students, cybersecurity professionals, digital-forensics practitioners, multimedia analysts, and artificial-intelligence developers working in video authentication and synthetic-media detection.

Zielgruppe

Research

Autoren/Hrsg.

Sheikh Abdullah, Siti Norul Huda

Alrawahneh, Ayat Abd Muti

Syed Abdullah, Sharifah Nurul Asyikin

Taylor, Sarah Khadijah

Herawan, Tutut

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Computerkriminalität & Hacking

Inhaltsverzeichnis

CHAPTER 1 INTRODUCTION TO VIDEO AUTHENTICATION AND DETECTION TECHNIQUES    1.- CHAPTER 2 VIDEO MANIPULATION DETECTION USING CNN-LSTM DUAL STAGE METHOD FOR OBJECT FORGERY.- CHAPTER 3 VIDEO AUTHENTICATION BASED ON QUANTIZATION AND DEEP LEARNING METHODS.- CHAPTER 4 METADATA AND FILE SIGNATURE ANALYSIS FOR VIDEO AUTHENTICATION.-CHAPTER 5 VIDEO AUTHENTICATION USING PHOTO-RESPONSE NON-UNIFORMITY.-etc.

Über Autor(innen)

Siti Norul Huda Sheikh Abdullah graduated from the University of Manchester Institute of Science and Technology in the United Kingdom with a first degree in computing. She continued her master’s degree in artificial intelligence at Universiti Kebangsaan Malaysia. She later pursued a Ph.D. in Computer Vision at Universiti Teknologi Malaysia under Faculty of Electrical Engineering. As Chairperson of the Cyber Security Academia Malaysia, she participated in both domestic and international initiatives such as UNoDC, FIRA, Asian Foundation, IMWU, DFRS, MIAMI, MACE, and IDB Alumni. She was elected as the deputy dean (Research and Innovation) of the Faculty of Information Science and Technology at Universiti Kebangsaan Malaysia after serving as the chairperson of the Centre for Cyber Security from 2017 to 2020. Pattern recognition, cybersecurity, and computer vision are the main areas of her study.

Ayat Abd-Muti Alrawahneh received her first degree in Computer Engineering from the University of Jordan in 2011. She furthered her master’s studies in Artificial Intelligence at Universiti Sultan Zainal Abidin (UniSZA), Malaysia, completing them in 2022. She completed her PhD studies in Artificial Intelligence at Universiti Kebangsaan Malaysia (UKM) in 2026. She is currently a research assistant at Universiti Kebangsaan Malaysia, contributing to deep learning and computer vision projects. Ayat has actively conducted national and international training sessions in IT and programming, delivering impactful educational courses to diverse audiences. She has served in various capacities, including quality assurance engineer, IT trainer, and student affairs administrator, highlighting her ability to bridge technical expertise with practical application. Her research interests include computer vision and AI-driven solutions. She has published in international journals and conferences, contributing to the advancement of AI applications in education and technology.

Sharifah Nurul Asyikin Syed Abdullah is a senior analyst in digital forensics at CyberSecurity Malaysia. She holds a bachelor’s degree from the National University of Malaysia (UKM) and a master of Business Administration from the University of Malaya (UM). In her role, she specializes in analyzing digital evidence, including video and image forensics. She also leads the Vehicle Forensics Project, which supports investigations by preserving and analyzing data from vehicles at crime scenes. As a subject matter expert, she has presented findings on digital evidence in court as an expert witness, contributing to the resolution of complex cases. Her education and expertise have positioned her as a key professional in the field of digital forensics.

Sarah Khadijah Taylor is a digital forensics specialist with more than 15 years of experience in the field. She is currently working for CyberSecurity Malaysia. She has authored several digital forensics guidelines, including the ISO 27037, INTERPOL Global Guidelines for Digital Forensics Laboratories, United Nations Digital Evidence Best Practice Guide and INTERPOL Guidelines for Seizing Virtual Assets. She has successfully led several digital forensics labs into achieving ISO 17025:2017 accreditation, including Oman, Brunei, and Uzbekistan. Apart from that, she is a digital forensics consultant for United Nations Office of Drugs and Crime (UNODC) and adjunct lecturer for master’s program in several local universities.

Tutut Herawan is an associate professor at the Department of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaya, Malaysia. He was named in the Top 2% World Scientists Ranking by Stanford University and Elsevier BV, since 2020–present. He received a Ph.D. degree in information technology from Universiti Tun Hussein Onn Malaysia in 2010. He has more than 20 years experiences as academic staff and has supervised many master and Ph.D. students. He is the associate editor of many international journals of Scopus and Clarivate Web of Science indexes. He has edited many books and published more than 360 articles in various book chapters, international journals, and conference proceedings. He is an active reviewer for many reputable international journals.