Machine Learning in Image Steganalysis

• Main Author: Schaathun, Hans Georg
• Format: eBook Book
• Language: English
• Published: Chichester, West Sussex Wiley 2012; WILEY; IEEE Press : Wiley; John Wiley & Sons, Incorporated; Wiley-IEEE Press; Wiley-Blackwell; Institution of Electrical Engineers; John Wiley & Sons Ltd
• Edition: 1
• Series: Wiley - IEEE
• Subjects: Data encryption (Computer science); Machine learning; SCIENCE; SCIENCE / Waves & Wave Mechanics; Signal Processing and Analysis; Wavelets (Mathematics); Waves & Wave Mechanics
• ISBN: 9780470663059; 0470663057; 9781118437964; 1118437969; 9781118437988; 1118437985; 1118437950; 9781118437957
• DOI: 10.1002/9781118437957

<p><i>Steganography</i> 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. S<i>teganalysis</i> 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. </p> <p><b>Part 1</b>of 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. <b>Part 2</b> is a survey of a wide range of feature vectors proposed for steganalysis with performance tests and comparisons. <b>Part 3</b> 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.</p> <p>Key features: </p> <ul> <li>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.</li> <li>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. </li> <li>Contains Python programs and algorithms to allow the reader to modify and reproduce outcomes discussed in the book.</li> <li>Includes companion software available from the author’s website.</li> </ul>