Overview

Steganography is the art and science of hiding information in inconspicuous cover data so that even the existence of a secret message is kept confidential, and steganalysis is the task of detecting secret messages in covers. This research monograph focuses on the role of cover signals, the distinguishing feature that requires us to treat steganography and steganalysis differently from other secrecy techniques. The main theoretical contribution of the book is a proposal to structure approaches to provably secure steganography according to their implied assumptions on the limits of the adversary and on the nature of covers. A further contribution is the emphasis on dealing with heterogeneity in cover distributions, crucial for security analyses. The author's work complements earlier approaches based on information, complexity, probability and signal processing theory, and he presents numerous practical implications. The scientific advances are supported by a survey of the classical steganography literature; a new proposal for a unified terminology and notation that is maintained throughout the book; a critical discussion of the results achieved and their limitations; and an assessment of the possibility of transferring elements of this research's empirical perspective to other domains in information security. The book is suitable for researchers working in cryptography and information security, practitioners in the corporate and national security domains, and graduate students specializing in multimedia security and data hiding.

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9783642264504

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''This excellent book provides a detailed account of recent advances in statistical steganalysis ... This book provides a valuable resource for security practitioners, researchers, and graduate students''. (Alessandro Berni, ACM Computing Reviews, 3/3/2011)

<p>''This excellent book provides a detailed account of recent advances in statistical steganalysis ... This book provides a valuable resource for security practitioners, researchers, and graduate students''. (Alessandro Berni, ACM Computing Reviews, 3/3/2011)

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