摘要
Stochastic modulation steganography embeds secret message within the cover image by adding stego-noise with a specific probabilistic distribution. No method is known to be applicable to the estimation of stochastic modulation steganography. By analyzing the distributions of the horizontal pixel difference of images before and after stochastic modulation embedding, we present a new steganalytic approach to accurately estimate the length of secret message in stochastic modulation steganography. The pro- posed method first establishes a model describing the statistical relationship among the differences of the cover image, stego-image and stego-noise. In the case of stegoimage-only steganalysis, rough estimate of the distributional parameters of the cover image＇s pixel difference is obtained with the use of the provided stego-image. And grid search and Chi-square goodness of fit test are exploited to estimate the length of the secret message embedded with stochastic modulation steganography. The experimental results demonstrate that our new approach is effective for steganalyzing stochastic modulation steganography and accurately estimating the length of the secret message.
Stochastic modulation steganography embeds secret message within the cover image by adding stego-noise with a specific probabilistic distribution. No method is known to be applicable to the estimation of stochastic modulation steganography. By analyzing the distributions of the horizontal pixel difference of images before and after stochastic modulation embedding, we present a new steganalytic approach to accurately estimate the length of secret message in stochastic modulation steganography. The pro- posed method first establishes a model describing the statistical relationship among the differences of the cover image, stego-image and stego-noise. In the case of stegoimage-only steganalysis, rough estimate of the distributional parameters of the cover image＇s pixel difference is obtained with the use of the provided stego-image. And grid search and Chi-square goodness of fit test are exploited to estimate the length of the secret message embedded with stochastic modulation steganography. The experimental results demonstrate that our new approach is effective for steganalyzing stochastic modulation steganography and accurately estimating the length of the secret message.
基金
supported by the National Natural Science Foundation of China(Grant Nos.60325208,90604008)
the Natural Science Foundation of Guangdong Province(Grant No.04205407).
