Name
Abstract | ||
|---|---|---|
This paper proposed a JPEG steganalysis scheme based on Markov model using features derived from the detected image and the estimated image. Estimated image is created by cropping four pixels of the detected image from left line. And the estimated image is similar with the original image with the statistical characteristics. From both of the detected image and estimated image, Markov process is applied to modeling the difference JPEG 2-D arrays along horizontal, vertical, and diagonal directions so as to utilize the high order statistics for enhancing changes caused by JPEG steganography. Support vector machines (SVM) are utilized as classifier. The experimental results have proved that the proposed method is effective in attacking by the existing steganalyzers. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14831-6_38 | ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS |
Keywords | Field | DocType |
JPEG steganalysis,Estimated image,Markov process,Difference JPEG 2-D arrays,Support vector machines (SVM) | Steganography,Maximum-entropy Markov model,Pattern recognition,Markov model,Computer science,JPEG,Artificial intelligence,Variable-order Markov model,Pixel,Steganalysis,Hidden Markov model | Conference |
Volume | ISSN | Citations |
93 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuai Zhang | 1 | 37 | 11.44 |
| Hongbin Zhang | 2 | 0 | 0.34 |