Defending Against Statistical Steganalysis

The main purpose of steganography is to hide the occurrence of communication. While most methods in use today are invisible to an observer's senses, mathematical analysis may reveal statistical anomalies in the stego medium. These discrepancies expose the fact that hidden communication is happening.

This paper presents improved methods for information hiding. One method uses probabilistic embedding to minimize modifications to the cover medium. Another method employs error-correcting codes, which allow the embedding process to choose which bits to modify in a way that decreases the likelihood of being detected. In addition, we can hide multiple data sets in the same cover medium to provide plausible deniability.

To prevent detection by statistical tests, we preserve the statistical properties of the cover medium. After applying a correcting transform to an image, statistical steganalysis is no longer able to detect the presence of steganography. We present an a priori estimate to determine the amount of data that can be hidden in the image while still being able to maintain frequency count based statistics. This way, we can quickly choose an image in which a message of a given size can be hidden safely. To evaluate the effectiveness of our approach, we present statistical tests for the JPEG image format and explain how our new method defeats them.