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Machine Learning in Image Steganalysis
book

Machine Learning in Image Steganalysis

by Hans Georg Schaathun
October 2012
Intermediate to advanced
304 pages
8h 22m
English
Wiley-IEEE Press
Content preview from Machine Learning in Image Steganalysis

Chapter 14

The Steganalysis Problem

So far, we have defined steganalysis as the eavesdropper's problem, deciding whether or not a given information object contains covert information in addition to the overt information. In reality, the eavesdropper's problem is not so homogeneous. Different scenarios may require different types of steganalysis, and sometimes the eavesdropper needs more information about the covert message.

Generally, the difficulty of steganalysis decreases with the size of the covert message. An important question from the steganographer's point of view is ‘how much data can be embedded and still remain undetectable?’ This maximum quantity of undetectable information may be called the steganographic capacity. The concept of undetectable is a fuzzy concept, giving rise to a number of proposed security criteria.

In this chapter, we will discuss various use cases and how they call for different properties in steganalysers. We will also see how composite steganalytic systems can be designed, using multiple constituent steganalysers.

14.1 Different Use Cases

14.1.1 Who are Alice and Bob?

In the original phrasing of the problem, Alice and Bob are prisoners who want to use steganography to coordinate escape plans under the nose of Wendy. Already arrested, Alice and Bob are not necessarily assumed to be innocent. It is quite possible that Wendy does not need very strong evidence to withdraw their privilege by closing the communication line between Alice and Bob, and ...

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Publisher Resources

ISBN: 9781118437988