Steganography is the process of hiding data into public digital medium for secret
communication. The image in which the secret data is hidden is termed
as stego image. The detection of hidden embedded data in the image is the
foundation for blind image steganalysis. The appropriate selection of cover
file type and composition contribute to the successful embedding. A large
number of steganalysis techniques are available for the detection of steganography
in the image. The performance of the steganalysis technique depends
on the ability to extract the discriminative features for the identification of
statistical changes in the image due to the embedded data. The issue encountered
in the blind image steganography is the non-availability of knowledge
about the applied steganography techniques in the images. This paper surveys
various steganalysis methods, different filtering based preprocessing methods,
feature extraction methods, and machine learning based classification methods,
for the proper identification of steganography in the image.
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