Title :
JPEG image steganalysis method based on binary similarity measures
Author :
Lin, Jing-Qu ; Zhong, Shang-ping
Author_Institution :
Coll. of Math. & Comput. Sci., Fuzhou Univ., Fuzhou, China
Abstract :
Many JPEG steganography techniques are used to communicate secret messages by terrorists that threaten the security of a nation. So steganalysis is very important. Avcibas proposed a steganalysis based on binary similarity measures which only work well on LSB-based steganography and derived features from the spatial domain of images. This paper proposes a novel usage of binary similarity measures in JPEG steganalysis. The method captures the seventh and eighth bit planes of the non-zero DCT coefficients from JPEG images and computes 14 features of each image based on binary similarity measures. These features are used to construct a support vector machine classifier which can distinguish between stego images and cover images. The experiment results are presented to demonstrate that the proposed scheme has lower computational complexity and the same high detecting accuracy.
Keywords :
discrete cosine transforms; feature extraction; image classification; image coding; message authentication; steganography; support vector machines; JPEG image steganalysis; binary similarity measure; computational complexity; discrete cosine transform; secret message; support vector machine; Computational complexity; Cybernetics; Discrete cosine transforms; Educational institutions; Machine learning; Mathematics; Steganography; Support vector machine classification; Support vector machines; Transform coding; Binary similarity measure; JPEG; Steganalysis; Steganography; Support vector machine;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212213
