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In this paper, we propose an extended pairs of values analysis to detect and estimate the amount of secret messages embedded with 2LSB replacement in digital images based on chi-square attack and regularity rate in pixel values. The detection process is separated from the estimation of the hidden message length, as it is the main requirement of any steganalysis method. Hence, the detection process acts as a discrete classifier, which classifies a given set of images into stego and clean classes. The method can accurately detect 2LSB replacement even when the message length is about 10% of the total capacity, it also reaches its best performance with an accuracy of higher than 0.96 and a true positive rate of more than 0.997 when the amount of data are 20% to 100% of the total capacity. However, the method puts no assumptions neither on the image nor the secret message, as it tested with two sets of 3000 images, compressed and uncompressed, embedded with a random message for each case. This method of detection could also be used as an automated tool to analyse a bulk of images for hidden contents, which could be used by digital forensics analysts in their investigation process.

Detecting 2LSB steganography using extended pairs of values analysis