Attacks on Steganographic Systems
IH '99 Proceedings of the Third International Workshop on Information Hiding
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Steganalysis of JPEG Images: Breaking the F5 Algorithm
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
IH'04 Proceedings of the 6th international conference on Information Hiding
Optimized Feature Extraction for Learning-Based Image Steganalysis
IEEE Transactions on Information Forensics and Security
Steganalysis using image quality metrics
IEEE Transactions on Image Processing
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In this paper, a universal steganalysis scheme for JPEG images based upon joint transform features is presented. We first analyzed two different transform domains (Discrete Cosine Transform and Discrete Wavelet Transform) separately, to extract features for steganalysis. Then a combination of these two feature sets is constructed and employed for steganalysis. A Fisher Linear Discriminant classifier is trained on features from both clean and steganographic images using all three feature sets and subsequently used for classification. Experiments performed on images embedded with two variants of F5 and Model based steganographic techniques reveal the effectiveness of proposed steganalysis approach by demonstrating improved detection for joint features.