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Binary Image Steganalysis Based on Symmetrical Local Residual Patterns
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Residual computation is an effective method for gray-scale image steganalysis.For binary im-ages,the residual computation calculated by the XOR op-eration is also employed in the local residual patterns(LRP)model for steganalysis.A binary image steganalyt-ic scheme based on symmetrical local residual patterns(SLRP)is proposed.The symmetrical relationships among residual patterns are introduced that make the features more compact while reducing the dimensionality of the features set.Multi-scale windows are utilized to construct three SLRP submodels which are further merged to con-struct the final features set instead of a single model.SLRPs with higher probability to be modified after em-bedding are emphasized and selected to construct the fea-ture sets for training the support vector machine classifi-er.The experimental results show that the proposed steganalytic scheme is effective for detecting binary im-age steganography.
Information hidingSteganalysisSymmetrical local residual patternsMulti-scale model
LUO Junwei、YU Mujian、YIN Xiaolin、LU Wei
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School of Computer Science and Engineering,Guangdong Province Key Laboratory of Information Security Technology,Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing,Sun Yat-sen University,Guangzhou 510006,China
国家自然科学基金国家自然科学基金国家自然科学基金Key Areas Research and Development Program of Guangdong
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