Block-based image steganalysis: Algorithm and performance evaluation

• Published in: 2010 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 1679 - 1682
• Main Authors: Seongho Cho, Byung-Ho Cha, Jingwei Wang, Kuo, C.-C J
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2010
• Subjects: Classification tree analysis; Convergence; Discrete cosine transforms; Feature extraction; Image sampling; Markov processes; Steganography; Testing; Vector quantization; Voting
• ISBN: 1424453089; 9781424453085
• ISSN: 0271-4302; 2158-1525
• DOI: 10.1109/ISCAS.2010.5537499

Traditional image steganalysis techniques are conducted with respect to the entire image. In this work, we aim to differentiate a stego image from its cover image based on steganalysis results of decomposed image blocks. As a natural image often consists of heterogeneous regions, its decomposition will lead to smaller image blocks, each of which is more homogeneous. We classify these image blocks into multiple classes and find a classifier for each class to decide whether a block is from a cover or stego image. Consequently, the steganalysis of the whole image can be conducted by fusing steganalysis results of all image blocks through a voting process. Experimental results will be given to show the advantage of the proposed block-based image steganalysis approach.