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Information Technology Journal

Year: 2014 | Volume: 13 | Issue: 16 | Page No.: 2588-2592
Research Article

Steganalysis of Highly Undetectable Steganography Using Convolution Filtering

Jiaohua Qin
College of Computer Science and Information Technology,Central South University of Forestry and Technology, Changsha, 410004, China
Xuyu Xiang
College of Computer Science and Information Technology,Central South University of Forestry and Technology, Changsha, 410004, China
Yu Deng
College of Computer Science and Information Technology,Central South University of Forestry and Technology, Changsha, 410004, China
Youyun Li
School of Traffic and Transportation,Changsha University of Science and Technology, Changsha, 410004, China
Lili Pan
College of Computer Science and Information Technology,Central South University of Forestry and Technology, Changsha, 410004, China
Highly undetectable steganography (HUGO) is one of the most advanced steganographic systems. A new methodology of steganalysis is presented against HUGO for digital images. The proposed method first obtains textural features by applying local linear transformation of convolution filtering to the image. Then, the co-occurrence matrices are constructed from horizontal and vertical direction. Finally, the ensemble classifier is used to classify. Experimental results show that the proposed steganalysis system is significantly superior to the prior arts on the detection performance and computational time.
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