Machine Learning
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
A Secure Data Hiding Scheme for Two-Color Images
ISCC '00 Proceedings of the Fifth IEEE Symposium on Computers and Communications (ISCC 2000)
Defending against statistical steganalysis
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
Blind Multi-Class Steganalysis System Using Wavelet Statistics
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 02
Color Image Steganography Based on Module Substitutions
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 02
Multi-class Blind Steganalysis Based on Image Run-Length Analysis
IWDW '09 Proceedings of the 8th International Workshop on Digital Watermarking
A Markov process based approach to effective attacking JPEG steganography
IH'06 Proceedings of the 8th international conference on Information hiding
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
IH'04 Proceedings of the 6th international conference on Information Hiding
Using image steganography for decryptor distribution
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part I
ISPEC'05 Proceedings of the First international conference on Information Security Practice and Experience
Steganalysis based on differential statistics
CANS'06 Proceedings of the 5th international conference on Cryptology and Network Security
Data hiding in binary image for authentication and annotation
IEEE Transactions on Multimedia
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Identifying steganographic payload location in binary image
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
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In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.