25-08-2017, 09:32 PM
F5—A Steganographic Algorithm High Capacity Despite Better Steganalysis
F5 Steganography.pdf (Size: 232 KB / Downloads: 29)
Introduction
Secure steganographic algorithms hide confidential messages within other, more
extensive data (carrier media). An attacker should not be able to find out, that
something is embedded in the steganogram (i. e., a steganographically modified
carrier medium) [8].1
Visual attacks on steganographic systems are based on essential information
in the carrier medium that steganographic algorithms overwrite [5]. Adaptive
techniques (that bring the embedding rate in line with the carrier content)
prevent visual attacks, however, they also reduce the proportion of steganographic
information in a carrier medium. Lossy compressed carrier media (JPEG,
MP3, . . . ) are originally adaptive and immune against visual (and auditory respectively)
attacks.
JPEG File Interchange Format
The file format defined by the Joint Photographic Experts Group (JPEG) stores
image data in lossy compressed form as quantised frequency coefficients. Fig. 1
shows the compressing steps performed. First, the JPEG compressor cuts the
uncompressed bitmap image into parts of 8 by 8 pixels. The discrete cosine
transformation (DCT) transfers 8 × 8 brightness values into 8 × 8 frequency
coefficients (real numbers). After DCT, the quantisation suitably rounds the
frequency coefficients to integers in the range −2048 . . . 2047 (lossy step). The
histogram in Fig. 2 shows the discrete distribution of the coefficient’s frequency
of occurrence.
If we look at the distribution in Fig. 2, we can recognise two characteristic
properties:
Matrix Encoding
Ron Crandall [1] introduced matrix encoding as a new technique to improve the
embedding efficiency. F5 possibly is the first implementation of matrix encoding.
If most of the capacity is unused in a steganogram, matrix encoding decreases the
necessary number of changes. Let us assume that we have a uniformly distributed
secret message and uniformly distributed values at the positions to be changed.
One half of the message causes changes, the other half does not. Without matrix
encoding, we have an embedding efficiency of 2 bits per change. Because of the
shrinkage produced by F4, the embedding efficiency is even a bit lower, e. g.
1.5 bits per change.
Conclusion
Many steganographic algorithms offer a high capacity for hidden messages, but
are weak against visual and statistical attacks. Tools withstanding these attacks
provide only a very small capacity. The algorithm F4 combines both preferences:
resistance against visual and statistical attacks as well as high capacity. Matrix
encoding and permutative straddling enable the user to decrease the necessary
number of steganographic changes and to equalise the embedding rate in the
steganogram. F5 accomplishes a steganographic proportion that exceeds 13%
of the JPEG file size (cf.Table3). Please understand this result as a friendly
provocation for security analysts.