Steganalytic attack for an adaptive steganography using support vector machine

Abstract

Steganographic techniques have been used for centuries. Using steganography, secret messages can be embedded inside a piece of unsuspicious information and sending it without anyone's knowledge about the existence of the secret message. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can lead to the prevention of disastrous security incidents. Steganalysis can be a targeted steganalysis or a blind steganalysis. In the existing method, adaptive steganography algorithm is used to provide larger embedding capacity based on image contrast. In this paper, a new technique is implemented to calculate the length of embedded message using Support Vector Machine to classify the cover and stego images with extremely low computational cost of comparing the bit positions.