Security '01 Abstract
Defending Against Statistical Steganalysis
Niels Provos, Center for Information Technology Integration, University of Michigan
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
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.
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