Computing Dependencies between DCT Coefficients for Natural Steganography in JPEG Domain

Abstract

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 de- mosaicking, 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 pseudo-embedding 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.