This research aims to design and implement a Steganalysis system that scan and test images, each of 24-bit, to find out if it contains hidden information. Using of wavelet transformation of Haar wavelet type to transform the images from the spatial domain to the frequency domain to produce feature vectors of coefficients, these coefficients are mapped, then using the ability of Probability Density Function (PDF) to minimize the features to extract the most important features that will be used as an input to the statistical tests in both The Standard statistics and the first order statistics
The Standard statistics are Absolute Value Differences (AD), Mean Square Error (MSE), Signal- to- Noise Ratio (SNR), Peak Signal- to- Noise Ratio (PSNR), Normalized Cross –Correlation (NCC), Correlation Quality (CQ).and the order statistics Mean, Variance, Skewness, Kurtosis. These tools are useful in examine the difference and similarity between the origin image and the suspected image.
The images that had been tested are 12 BMP images with different sizes, which had information hiding both Steganography and watermarked. Each BMP image of 24-bit. The stego objects(hidden information) are embedded using S-Toll, and Developed Steganography tool that modifying Least Significant Bit (LSB) of the pixel, some were detected and some were not, 6 images had information hiding and 6 were clear, 3 of 12 (i.e. 33%)were pass as they were clear, while 2 images were not. The others were detected. The developed system is implemented using Visual Basic programming language version 6, provides by Windows environments (XP, Me), and the resulted obtained are encouraging. |