Download e-book for kindle: Advanced Statistical Steganalysis by Rainer Böhme

Posted On February 23, 2018 at 3:49 pm by / Comments Off on Download e-book for kindle: Advanced Statistical Steganalysis by Rainer Böhme

By Rainer Böhme

ISBN-10: 3642143121

ISBN-13: 9783642143120

ISBN-10: 364214313X

ISBN-13: 9783642143137

Steganography is the paintings and technology of hiding info in inconspicuous conceal information in order that even the lifestyles of a mystery message is stored private, and steganalysis is the duty of detecting mystery messages in covers. This examine monograph specializes in the function of canopy signs, the distinguishing function that calls for us to regard steganography and steganalysis otherwise from different secrecy ideas. the most theoretical contribution of the ebook is a suggestion to constitution methods to provably safe steganography in accordance with their implied assumptions at the limits of the adversary and at the nature of covers. one other contribution is the emphasis on facing heterogeneity in conceal distributions, an important for protection analyses. The author's paintings enhances prior methods in keeping with details, complexity, chance and sign processing idea, and he offers a number of sensible implications. The medical advances are supported via a survey of the classical steganography literature; a brand new idea for a unified terminology and notation that's maintained in the course of the publication; a severe dialogue of the implications completed and their boundaries; and an review of the potential of shifting components of this research's empirical standpoint to different domain names in details protection. The publication is appropriate for researchers operating in cryptography and data safety, practitioners within the company and nationwide protection domain names, and graduate scholars focusing on multimedia safety and information hiding.

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Operator E(X) stands for the expected value of its argument X. X ∼ N (μ, σ) means that random variable X is drawn from a Gaussian distribution with mean μ and standard deviation σ. Analogously, we write N (μ, Σ) for the multivariate case with covariance matrix Σ. When convenient, we also use probability spaces (Ω, P) on the right-hand side of operator ‘∼’, using the simplified notation (Ω, P) = (Ω, P(Ω), P) since the set of events is implicit for countable sample spaces. , all integers i : a ≤ i ≤ b are equally probable).

In this scenario, the (i ) (i ) steganalyst inspects a set of suspect objects {x1 1 , . . , xNN } and has to decide whether steganography is used in any of them or not at all. This scenario corresponds to a situation where a storage device, on which secret data may be hidden in anticipation of a possible confiscation, is seized. In this setting, sender and recipient may be the same person. , to find the least-detectable sequence (i1 , . . , iN ), as well as the optimal aggregation of evidence from N runs of Detect.

2 (b)). In this case it is particularly hard to compare different methods objectively. As a remedy, many metrics derived from the ROC curve have been proposed to express steganographic security (or steganalysis performance) on a continuous scale, most prominently, • the detector reliability as area under the curve (AUC), minus the triangle below the 45◦ line, scaled to the interval [0, 1] (a measure of insecurity: values of 1 imply perfect detectability) [68], • the false positive rate at 50% detection rate (denoted by FP50 ), • the equal error rate EER = α ⇔ α = β, α+β • the total minimal decision error TMDE = minτ [87], and 2 • the minimum of a cost- or utility-weighted sum of α and β whenever dependable weights are known for a particular application (for example, false positives are generally believed to be more costly in surveillance scenarios).

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Advanced Statistical Steganalysis by Rainer Böhme

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