Keywords : Stegnoanalysis

Neural Network Using for Extracting Hidden Information in Images

safwan hasoon; Farhad M. Khalifa

AL-Rafidain Journal of Computer Sciences and Mathematics, 2013, Volume 10, Issue 3, Pages 113-130
DOI: 10.33899/csmj.2013.163539

Steganography technique widely spread and varied. With the widening in using steganography, its misuse alarmists arisen. Thus steganalysis comes into sight to deter unwanted secret communications.
In this paper a new scheme proposed for extracting hidden information, this scheme relies on the capability of artificial neural networks for prediction to estimate the original values of the pixels which values of some of them were changed by the affection of data embedding process, and then the present pixel values will be compared with estimated values to identify the embedded data. Multilayer Perceptron MLP neural network used in this scheme to estimate the pixel's original value using its neighbor pixels. The proposed schemes programmed using Matlab v. The proposed schemes has been trained and tested using a data base prepared for this purpose. Then its performance compared with another work in the same field applied in similar conditions. The results showed that the proposed scheme has the ability to achieving the desired with a good rate of success.

Steganalysis Using KL Transform and Radial Basis Neural Network

Safwan Hasoon; Farhad M. Khalifa

AL-Rafidain Journal of Computer Sciences and Mathematics, 2012, Volume 9, Issue 1, Pages 47-58
DOI: 10.33899/csmj.2012.163670

The essential problem in the security field is how to detect information hiding. This paper proposes a new steganalysis scheme based on artificial neural network as a classifier to detect information hiding in colored and grayscale images. The statistical features extracted from Karhunen-Loève (KL) transform coefficients obtained from co-occurrence matrix of image. Then radial basis neural network (RBNN) trained using these features to discriminate  whether the image contains hidden information or not. This system can be used to prevent the suspicious secret communication.