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Steganalysis of Jsteg algorithm based on a novel statistical model of quantized DCT coefficients
- Source :
- 2013 20th IEEE International Conference on Image Processing (ICIP), 2013 20th IEEE International Conference on Image Processing (ICIP), Sep 2013, Melbourne, Australia. pp.4427-4431, ⟨10.1109/ICIP.2013.6738912⟩, ICIP
- Publication Year :
- 2013
- Publisher :
- HAL CCSD, 2013.
-
Abstract
- International audience; The goal of the paper is to propose an optimal statistical test for the steganalysis of Jsteg algorithm. The test is based on a state-of-the-art statistical model of quantized Discrete Cosine Transform (DCT) coefficients that allows us to reliably detect any small change in a cover image due to hidden information. By formulating the hidden information detection as a hypothesis testing problem, the paper designs the most powerful Likelihood Ratio Test (LRT) assuming that all model parameters are perfectly known. The statistical performance of the LRT is analytically provided. Numerical results and comparison with other detectors highlight the relevance of the proposed approach.
- Subjects :
- Steganalysis
021110 strategic, defence & security studies
Steganography
business.industry
0211 other engineering and technologies
Pattern recognition
Statistical model
02 engineering and technology
Image (mathematics)
Likelihood-ratio test
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
0202 electrical engineering, electronic engineering, information engineering
Discrete cosine transform
020201 artificial intelligence & image processing
Relevance (information retrieval)
Artificial intelligence
business
Algorithm
Mathematics
Statistical hypothesis testing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- 2013 20th IEEE International Conference on Image Processing (ICIP), 2013 20th IEEE International Conference on Image Processing (ICIP), Sep 2013, Melbourne, Australia. pp.4427-4431, ⟨10.1109/ICIP.2013.6738912⟩, ICIP
- Accession number :
- edsair.doi.dedup.....aff9f2c386682b230dbf9d7e299a37cd