Steganalysis
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ABSTRACT
Data hiding has always been necessary. Encryption is a method used for most data communication in modern times but steganography has been used for years and is still being used to this date. The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message. If suspicion is raised, then this goal is defeated. Discovering and rendering useless such covert messages is a new art form known as steganalysis. Stego object is the object with hidden data.
To discover such covert messages we are using two types of attacks generally known as known-cover attack and stego only attack.
In known-cover attack both the original and stego object both are available. Thus the difference between the two objects (images) can be calculated by image difference algorithm (difference between the color components). In stego-only attack only the stego object (image) is available.
Algorithm we are implementing is a stego -only attack in LSB insertion for uncompressed color images encoded in 24 bit BMP format. The detection theory is based on statistical analysis of pixel pairs using their RGB components. The threshold value depends on correlation between pixel pairs in terms of color components. The probability of false detection rate and false alarm rate are detected.
For JPEG, we will inspect the information hidden in the tags of the image. Also we will perform steganalysis for text files using line shifting method.
OBJECTIVE:
Basic Steps:
To apply different steganalysis techniques on stego-object in order to investigate the presence of hidden information.
Retrieve the hidden information from the stego-object
Goal of Project:
In order to capture the statistical artifacts and hence image to determine the presence of hidden messages, we propose a set of binary similarity measures between successive bit planes. The basic idea is that, the correlation between the bit-planes as well the binary texture characteristics within the bit-planes will differ between a stego-image and a cover-image. The seventh and eight bit planes, and possibly others are used to calculate these binary similarity measures. The proposed technique does not need a reference image and it works with both spatial and transform-domain embedding. The method is to exploits intrinsic statistical properties of images to reveal the presence of steganographic content.
The objective of the proposed project is to develop novel techniques and algorithms for document (TEXT FILE) and image (BMP, JPEG FILES) steganalysis.