Digital Image Forensics

Theory and Implementation

Aniket Roy, Rahul Dixit, Ruchira Naskar, Rajat Subhra Chakraborty (Autoren)

Buch | Hardcover

89 Seiten

2019 | 1st ed. 2020
Springer Verlag, Singapore
978-981-10-7643-5 (ISBN)

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This book discusses blind investigation and recovery of digital evidence left behind on digital devices, primarily for the purpose of tracing cybercrime sources and criminals. It presents an overview of the challenges of digital image forensics, with a specific focus on two of the most common forensic problems. The first part of the book addresses image source investigation, which involves mapping an image back to its camera source to facilitate investigating and tracing the source of a crime. The second part of the book focuses on image-forgery detection, primarily focusing on “copy-move forgery” in digital images, and presenting effective solutions to copy-move forgery detection with an emphasis on additional related challenges such as blur-invariance, similar genuine object identification, etc. The book concludes with future research directions, including counter forensics. With the necessary mathematical information in every chapter, the book serves as a useful reference resource for researchers and professionals alike. In addition, it can also be used as a supplementary text for upper-undergraduate and graduate-level courses on “Digital Image Processing”, “Information Security”, “Machine Learning”, “Computer Vision” and “Multimedia Security and Forensics”.

Aniket Roy is an M.S. (research) student at the Department of Computer Science and Engineering at the Indian Institute of Technology Kharagpur. He received his B.Tech. degree in Electronics and Communication Engineering from West Bengal University of Technology (now Maulana Abul Kalam Azad University of Technology), India in 2014. His primary research interest lies in multimedia security, reversible watermarking and digital forensics. He received the Best Paper Award at the 15th International Workshop on Digital-forensics and Watermarking. He is an IEEE student member. Rahul Dixit is a Ph.D. scholar at the Department of Computer Science and Engineering at the National Institute of Technology, Rourkela, India. He received his M.Tech. and B.Tech. degrees in Computer Science and Engineering from the Indian School of Mines, Dhanbad and Uttar Pradesh Technical University (now Dr. A.P.J. Abdul Kalam Technical University), respectively. His major research interests include digital image and video forensics, multimedia security and image processing. Ruchira Naskar has been an assistant professor at the National Institute of Technology Department of Computer Science and Engineering, Rourkela, India since 2014. She received her Ph.D. from the Indian Institute of Technology Kharagpur, India in 2014. Her primary research interests are multimedia security and digital rights management, and she has over 30 publications in reputed journals and conferences. Her recent research interest is Digital Forensics. Dr. Naskar is a Member of the IEEE. Rajat Subhra Chakraborty is an associate professor at the Indian Institute of Technology Kharagpur Department of Computer Science and Engineering, India. He has worked at National Semiconductor and Advanced Micro Devices (AMD). His research interests are in the areas of hardware security, very-large-scale integration (VLSI) design, digital watermarking and digital image forensics. He haspublished over 80 papers in respected international journals and conferences, and holds two U.S. patents. He has a Ph.D. in Computer Engineering from Case Western Reserve University (U.S.A.). Dr. Chakraborty is a senior member of the IEEE and the ACM.

Chapter 1: Introduction.- Chapter 2: Source Camera Identification Using Statistical Features.- Chapter 3: Copy Move Forgery Detection in Digital Images – A Survey and Analysis.- Chapter 4: Copy–Move Forgery Detection exploiting Statistical Image Features.- Chapter 5: Blur-invariant Copy-move Forgery Detection utilizing SWT-SVD.- Chapter 6: Copy–Move Forgery Detection with Similar but Genuine Objects using Texture Features.- Chapter 7: Conclusions and Future Work.

Erscheinungsdatum	04.06.2019
Reihe/Serie	Studies in Computational Intelligence ; 755
Zusatzinfo	32 Illustrations, color; 13 Illustrations, black and white; XVI, 89 p. 45 illus., 32 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Grafik / Design ► Digitale Bildverarbeitung
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Recht / Steuern ► Strafrecht ► Kriminologie
	Technik ► Elektrotechnik / Energietechnik
Schlagworte	Camera Source Identification • Copy-Move Forgery Detection • digital image forensics • Image forgery detection • Machine Learning based Classification • Similar But Genuine Objects
ISBN-10	981-10-7643-X / 981107643X
ISBN-13	978-981-10-7643-5 / 9789811076435
Zustand	Neuware