27 January 2010 Feature selection for steganalysis using the Mahalanobis distance
Author Affiliations +
Steganalysis is used to detect hidden content in innocuous images. Many successful steganalysis algorithms use a large number of features relative to the size of the training set and suffer from a "curse of dimensionality": large number of feature values relative to training data size. High dimensionality of the feature space can reduce classification accuracy, obscure important features for classification, and increase computational complexity. This paper presents a filter-type feature selection algorithm that selects reduced feature sets using the Mahalanobis distance measure, and develops classifiers from the sets. The experiment is applied to a well-known JPEG steganalyzer, and shows that using our approach, reduced-feature steganalyzers can be obtained that perform as well as the original steganalyzer. The steganalyzer is that of Pevn´y et al. (SPIE, 2007) that combines DCT-based feature values and calibrated Markov features. Five embedding algorithms are used. Our results demonstrate that as few as 10-60 features at various levels of embedding can be used to create a classifier that gives comparable results to the full suite of 274 features.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jennifer L. Davidson, Jennifer L. Davidson, Jaikishan Jalan, Jaikishan Jalan, "Feature selection for steganalysis using the Mahalanobis distance", Proc. SPIE 7541, Media Forensics and Security II, 754104 (27 January 2010); doi: 10.1117/12.841074; https://doi.org/10.1117/12.841074


The challenges of rich features in universal steganalysis
Proceedings of SPIE (March 21 2013)
Content-based indexing for medical image databases
Proceedings of SPIE (September 30 1998)
Application of conditional entropy measures to steganalysis
Proceedings of SPIE (February 14 2006)
Modern steganalysis can detect YASS
Proceedings of SPIE (January 27 2010)
Compression-based steganalysis of LSB embedded images
Proceedings of SPIE (February 14 2006)

Back to Top