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Steganalysis Using KL Transform and Radial Basis Neural Network | ||
| AL-Rafidain Journal of Computer Sciences and Mathematics | ||
| Article 4, Volume 9, Issue 1, 2012, Pages 47-58 PDF (711.54 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/csmj.2012.163670 | ||
| Authors | ||
| Safwan Hasoon; Farhad M. Khalifa | ||
| College of Computer Sciences and Mathematics University of Mosul | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| Stegnoanalysis; neural network; Steganography | ||
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