Abstract：The steganalysis method based on spacing statistics of short duplicate code is an efficient universal detection algorithm for LSB matching steganography.But the steganalysis method must select the appropriate dimension of short duplicate code to meet the different applications.This one-dimensionstatistical analysis method could not take into account the links between multivariate statistical features,thus may affect the detection capability.In this paper,a detection capability law of a single short duplicate code statistical feature is proved,and a method to reasonable choice of the short duplicate code dimension is presented to reduce the detection number.By analyzing the correlation between the statistical features of short duplicate code spacing statistics,a selected feature subset is described as a vector of local features.Then,a universal steganalysis method based on local features extracted from LSB sequences is proposed.The proposed steganalysis method uses the Gaussian Mixture Model (GMM) to describe the multi-dimensional local features,and designs classifier by integrating GMM generative model and SVM discriminative method based on global sequence vocabulary.The experimental results show that under the premise of effective control of the false alarm rate,the proposed method achieves the best overall detection performance to LSB matching steganography and to LSB replacement steganography.
钟尚平, 徐巧芬, 陈羽中, 何凤英. 一种基于LSB序列局部特征的通用隐写检测方法[J]. 电子学报, 2013, 41(2): 239-247.
ZHONG Shang-ping, XU Qiao-fen, CHEN Yu-zhong, HE Feng-ying. A Universal Steganalysis Method Based on Local Features Extracted from LSB Sequences. Chinese Journal of Electronics, 2013, 41(2): 239-247.
[1] 王朔中,张新鹏,张卫明.以数字图像为载体的隐写分析研究进展[J].计算机学报,2009,32(7):1247-1263. Wang Shuo-zhong,Zhang Xin-peng,et al.Recent advances in image-based steganalysis research[J].Chinese Journal of Computers,2009,32(7):1247-1263.(in Chinese) [2] 王国新,平西建,许漫坤,等.一种基于短重码间距 统计的隐写分析方法[J].中国科学F辑:信息科学,2009,39(4):416-421. Wang Guo-xin,Ping Xi-jian,Xu Man-kun,et al.A steganalysis method based on spacing statistics of short duplicate code [J].Science in China Series F:Information Sciences,2009,39(4):416-421.(in Chinese) [3] K Mikolajczyk,C Schmid.A performance evaluation of local descriptors[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2005,27(10):1615-1630. [4] J Zhang,M Marszalek,S Lazebnik,et al.Local features and kernels for classification of texture and object categories:A comprehensive study[J].International Journal of Computer Vision,2007,73(2):213-238. [5] 高常鑫,桑农.整合局部特征和滤波器特征的空间金字塔匹配模型[J].电子学报,2011,39(9):2034-2038. Gao Chang-xin,Sang Nong.Unifying local features and filterbank features in the spatial pyramid matching model[J].Acta Electronica Sinica,2011,39(9):2034-2038.(in Chinese) [6] Mario Fritz,Bastian Leibe,Barbara Caputo.Integrating representative and discriminant models for object category detection[A].Proceeding of the 10th IEEE Int Conf on Computer Vision[C].Beijing:IEEE Computer Society,2005.1363-1370. [7] Gabriella Csurka,Christopher R.Dance,Lixin Fan,et al.Visual categorization with bags of keypoints[A].Proceeding of the ECCV Int Workshop on Statistical Learning in Computer Vision[C].Prague,Czech Republic:Springer,2004.59-74. [8] Blei D,Ng A,Jordan M.Latent dirichlet allocation[J].Journal of Machine Learning Research,2003,3(5):993-1022. [9] Wikipedia.The free encyclopedia:Mixture model .http://en.wikipedia.org/wiki/Mixture_model,2011-11-3. [10] J Farquhar,S Szedmak,Hongying Meng,et al.Improving"bag-of-keypoints"image categorization[R].Technical report,University of Southampton,2005. [11] 郭立君,赵杰煜,史忠植.生成模型与判别方法相融合的图像分类方法[J].电子学报,2010,38(5):1141-1145. Guo Li-jun,Zhao Jie-yu,et al.Image categorization of Integrated generative models and discriminative methods[J].Acta Electronica Sinica,2010,38(5):1141-1145.(in Chinese) [12] S Theodoridis,K Koutroumbas.Pattern Recognition[M].Singapore:Elsevier Pte Ltd,2006.149-150. [13] CHENG Yong-qing,ZHUANG Yong-ming,YANG Jing-yu.Optimal fisher discriminant analysis using the rank decomposition[J].Pattern Recognition,1992,25(1):101-111. [14] USC SIPI.The USC-SIPI Image database[EB/OL].http://sipi.usc.edu/services/database/database.html,2011-11-20. [15] 陈铭,张茹,刘凡凡,等.基于区域相关性的LSB匹配隐写分析[J].通信学报,2010,31(3):1-11. Chen Ming,Zhang Ru,Liu Fan-fan,et al.Steganalysis of LSB matching based on regional correlation[J].Journal on Communications,2010,31(3):1-11.(in Chinese) [16] M.Figueiredo,A.Jain.Unsupervised learning of finite mixture models.IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(3):381-396. [17] 邓乃扬,田英杰.支持向量机-理论,算法与拓展[M].北京:科学出版社,2009.81-111. [18] 王朔中,张新鹏,张开文.数字密写和密写分析[M].北京:清华大学出版社,2005.20-23. [19] Menezes M,Oorschot P V,Vanstone S.Handbook of Applied Cryptography[M].CRC Press,1996.169-187. [20] 赵力.语音信号处理[M].北京:机械工业出版社,2010.228-230. [21] Chih-Chung Chang ,Chih-Jen Lin.LIBSVM-A library for support vector machines[EB/OL].http://www.csie.ntu.edu.tw/～cjlin/libsvm/,2011-10-3. [22] LUO Xiang-yang,WANG Dao-shun,WANG Ping,et al.A review on blind detection for image steganography[J].Signal Processing 88,2008:2138-2157.
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