Name
Abstract | ||
|---|---|---|
Calibration based attack is one of the most important steganalytic attacks in recent past specifically for JPEG domain steganography. In calibration attack, the attacker generally predicts the cover image statistics from the stego image. Preventing attackers from such prediction is used to resist these attacks. Domain separation (or randomization) is such a technique which is used for hiding the embedding domain from the attacker. It is observed that existing domain randomization techniques cannot provide enough randomization such that they are easily be detected by recent steganalysis techniques. In this paper, we have extended our previous work based on spatial desynchronization using statistical analysis. It is also experimentally shown that proposed algorithm is less detectable against the calibration based blind as well as targeted steganalytic attacks than the existing JPEG domain steganographic schemes. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s11042-012-1261-3 | Multimedia Tools and Applications |
Keywords | Field | DocType |
Steganography,Steganalysis,Calibration attack,Domain separation | Steganography,Embedding,Pattern recognition,Computer science,Algorithm,Randomization techniques,JPEG,Artificial intelligence,Steganalysis,Statistical analysis | Journal |
Volume | Issue | ISSN |
71 | 3 | 1380-7501 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arijit Sur | 1 | 67 | 19.19 |
| Devadeep Shyam | 2 | 0 | 1.01 |
| Piyush Goel | 3 | 68 | 17.91 |
| Jayanta Mukherjee | 4 | 378 | 56.06 |