TY - GEN
T1 - Computing dependencies between DCT coefficients for natural steganography in JPEG domain
AU - Taburet, Théo
AU - Bas, Patrick
AU - Fridrich, Jessica
AU - Sawaya, Wadih
N1 - Publisher Copyright: © 2019 Association for Computing Machinery.
PY - 2019/7/2
Y1 - 2019/7/2
N2 - This short paper is an extension of a family of embedding schemes called Natural Steganography, which embeds a message by mimicking heteroscedastic sensor noise in the JPEG domain. Under the assumption that the development from RAW uses linear demosaicking, we derive a closed-form for the covariance matrix of DCT coefficients from 3 × 3 JPEG blocks. This computation relies on a matrix formulation of all steps involved in the development pipeline, which includes demosaicking, conversion to luminance, DCT transform, and reordering. This matrix is then used for pseudoembedding in the JPEG domain on four lattices of 8 × 8 DCT blocks. The results obtained with the computed covariance matrix are contrasted with the results previously obtained with the covariance matrix estimated using Monte Carlo sampling and scaling. The empirical security using DCTR features at JPEG quality 100 increased from PE = 14% using covariance estimation and scaling to PE = 43% using the newly derived analytic form.
AB - This short paper is an extension of a family of embedding schemes called Natural Steganography, which embeds a message by mimicking heteroscedastic sensor noise in the JPEG domain. Under the assumption that the development from RAW uses linear demosaicking, we derive a closed-form for the covariance matrix of DCT coefficients from 3 × 3 JPEG blocks. This computation relies on a matrix formulation of all steps involved in the development pipeline, which includes demosaicking, conversion to luminance, DCT transform, and reordering. This matrix is then used for pseudoembedding in the JPEG domain on four lattices of 8 × 8 DCT blocks. The results obtained with the computed covariance matrix are contrasted with the results previously obtained with the covariance matrix estimated using Monte Carlo sampling and scaling. The empirical security using DCTR features at JPEG quality 100 increased from PE = 14% using covariance estimation and scaling to PE = 43% using the newly derived analytic form.
KW - Covariance
KW - Digital image steganography
KW - Image processing pipeline
KW - JPEG domain
KW - Sensor noise
UR - https://www.scopus.com/pages/publications/85069975293
U2 - 10.1145/3335203.3335715
DO - 10.1145/3335203.3335715
M3 - Conference contribution
T3 - IH and MMSec 2019 - Proceedings of the ACM Workshop on Information Hiding and Multimedia Security
SP - 57
EP - 62
BT - IH and MMSec 2019 - Proceedings of the ACM Workshop on Information Hiding and Multimedia Security
PB - Association for Computing Machinery, Inc
T2 - 7th ACM Workshop on Information Hiding and Multimedia Security, IH and MMSec 2019
Y2 - 3 July 2019 through 5 July 2019
ER -