Machine Learning in Image Steganalysis - Rilegato

Schaathun, Hans Georg

Rilegato

ISBN 10: 0470663057 ISBN 13: 9780470663059

Casa editrice: IEEE, 2012

Riassunto

Steganography is the art of communicating a secret message, hiding the very existence of a secret message. This book is an introduction to steganalysis as part of the wider trend of multimedia forensics, as well as a practical tutorial on machine learning in this context. It looks at a wide range of feature vectors proposed for steganalysis with performance tests and comparisons. Python programs and algorithms are provided to allow readers to modify and reproduce outcomes discussed in the book.

Su questo libro

Informazioni sull'autore

Hans Georg Schaathun, Department of Computing, University of Surrey, UK
Dr Schaathun was previously a lecturer in coding and cryptography at the University of Bergen. Since February 2006, he has been a lecturer at the University of Surrey, UK, belonging to the research group in Digital Watermarking and Multimedia Security. His main research areas are applications of coding theory in information hiding, and machine learning techniques in steganalysis. He teaches Computer Security and Steganography at MSc level, and Functional Programming Techniques at u/g level. Dr Scaathun has published more than 35 international, peer-reviewed articles, and is an associate editor of EURASIP Journal of Information Security.

Dalla quarta di copertina

Steganography is the art of communicating a secret message, hiding the very existence of a secret message. This is typically done by hiding the message within a non-sensitive document. Steganalysis is the art and science of detecting such hidden messages. The task in steganalysis is to take an object (communication) and classify it as either a steganogram or a clean document. Most recent solutions apply classification algorithms from machine learning and pattern recognition, which tackle problems too complex for analytical solution by teaching computers to learn from empirical data.

Part 1of the book is an introduction to steganalysis as part of the wider trend of multimedia forensics, as well as a practical tutorial on machine learning in this context. Part 2 is a survey of a wide range of feature vectors proposed for steganalysis with performance tests and comparisons. Part 3 is an in-depth study of machine learning techniques and classifier algorithms, and presents a critical assessment of the experimental methodology and applications in steganalysis.

Key features:

• Serves as a tutorial on the topic of steganalysis with brief introductions to much of the basic theory provided, and also presents a survey of the latest research.
• Develops and formalises the application of machine learning in steganalysis; with much of the understanding of machine learning to be gained from this book adaptable for future study of machine learning in other applications.
• Contains Python programs and algorithms to allow the reader to modify and reproduce outcomes discussed in the book.
• Includes companion software available from the author’s website.

Dettagli dell'edizione

• Editore: IEEE
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 0470663057
• ISBN 13: 9780470663059
• Rilegatura: Copertina rigida
• Numero di pagine: 284
• Contatto del produttore: Easy Access System Europe Oü, 16879218; gpsr.requests@easproject.com; ; Mustamäe tee 50, 10621, Tallinn, Estonia; Tallinn; 10621; Estonia