توضیحات
ABSTRACT
In this paper, we present a scheme based on feature mining and neuro-fuzzy inference system for detecting LSB matching steganography in grayscale images, which is a very challenging problem in steganalysis. Four types of features are proposed, and a Dynamic Evolving Neural Fuzzy Inference System (DENFIS) based feature selection is proposed, as well as the use of Support Vector Machine Recursive Feature Elimination (SVM-RFE) to obtain better detection accuracy.
INTRODUCTION
Steganalysis is the science and art of detecting the presence of hidden data in digital images,audios,videos and other media. In steganography or the hiding of secret data in digital media, the most common cover is digital images. To this date, many steganographical or embedding methods, such as LSB embedding, spread spectrum steganography, F5 algorithm and some other JPEG steganography, have been very successfully steganalyzed [Fridrich et al., 2003; Ker, 2005a; Fridrich et al. 2002; Harmsen and Pearlman 2003; Choubassi and Moulin 2005; Liu et al., 2006a].
Year:2007
Publisher:Proceedings of the 20th international joint conference on Artifical
By: Qingzhong Liu,Andrew H. Sung
File information: English Language / 6 Page / Size :113 KB
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سال:2007
ناشر:Proceedings of the 20th international joint conference on Artifical
کاری از: Qingzhong Liu,Andrew H. Sung
اطلاعات فایل: زبان انگلیسی/ 6 صفحه/ حجم 113 کیلوبایت
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