Abstract
We present a novel technique for steganalysis of images that have been subjected to embedding by steganographic algorithms. The seventh and eighth bit planes in an image are used for the computation of several binary similarity measures. The basic idea is that the correlation between the bit planes as well as the binary texture characteristics within the bit planes will differ between a stego image and a cover image. These telltale marks are used to construct a classifier that can distinguish between stego and cover images. We also provide experimental results using some of the latest steganographic algorithms. The proposed scheme is found to have complementary performance vis-à-vis Farid's scheme in that they outperform each other in alternate embedding techniques.
Highlights
Steganography refers to the science of “invisible” communication, where communication between two parties is undetectable by an eavesdropper
We have addressed the problem of steganalysis of images
We have developed a technique for discriminating between cover images and stego images obtained from various steganographic methods
Summary
Steganography refers to the science of “invisible” communication, where communication between two parties is undetectable by an eavesdropper. This is quite different from cryptography, where the goal is to make the content of the communications inaccessible to an eavesdropper. The subject is best explained in terms of the prisoner’s problem [2], where Alice and Bob are two inmates who wish to communicate in order to hatch an escape plan. In the general model for steganography we have Alice wishing to send a secret message m to Bob. In order to do so, she “embeds” m into a cover object c, to obtain the stego object s. The stego object is sent through the public channel
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