This text develops and formalizes the applications of machine learning in steganalysis. Researchers in steganalysis typically have a background in signal and image processing, or multimedia coding, and lack the high level statisticalknowledge required for using machine learning; this book provides an accessible introduction to the subject, as applied specifically to steganalysis. Much of the understanding of machine learning that can be gained from this book canbe adapted for future study of machine learning in other applications.Key features:The only book to look at steganalysis from the perspective of machine learning theory, and to apply the common technique of machine learning to the particular field of steganalysis; ideal for people working in both disciplines.An integrated approach throughout, with practical steganalytic examples to illustrate the theory.The authors’ background combines maths, coding, and machine learning with information hiding, meaning the complex statistical theory is made accessible to those new to machine learning.Presents both feature sets and different classifiers.Supported by MATLAB (or python) programs and algorithms to allow the reader to modify and reproduce outcomes discussed in the book.Acknowledges the importance of this particular topic within the wider field of digital forensics.Companion software available from the author’s website.
- ISBN: 978-0-470-66305-9
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 296
- Fecha Publicación: 28/09/2012
- Nº Volúmenes: 1
- Idioma: Inglés