Study of Image Steganalysis Techniques
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Abstract
With the emergence of steganography, the counter technology, namely steganalysis has also emerged. Steganalysis is used to detect or extract the hidden message from the carriers. It is a set of techniques: visual or statistical by which it is possible to check for the existence of steganography content in cover object. Steganalysis could be passive or active. Passive steganalysis simply aims to identify the presence or absence of secret message whereas Active steganalysis attempts to estimate the message length, secret key, message bits, etc. Current steganalysis techniques emphasize on the design of the classifier based on the training set of cover objects and stego objects obtained from a variety of different embedding algorithms. The inherent features of natural image get violated when an image undergoes some embedding process; classification is done on the basis of the some of these features. The extraction of sensitive features and design of good classifier are the principal tasks for steganalysis.
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Keywords: Steganalysis; Classifier; Feature extraction; RBFNN; LGEM; GEFR; LSB; GA; RS; POV
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