1.9 Steganalysis - bit-o-steg detection

Steganalysis

Bit-o-steg detection

Due to the complexity of bit-o-steg, we turned to previous research to find a viable detection method. Eachentry in the 8x8 blocks has a specific probability distribution. The distribution is found by looking at the values of that entryslot across the entire image. Figure 1 shows a histogram of an entry without data. The histogram looks at the DCT coefficientvalue and counts how often that value appears within that entry slot. Figure 2 shows a histogram of an entry with data. Comparingthe two figures, there is a sudden drop around the 0 value in the histogram of an entry with data. The histogram of an entry withdata also appears to smooth out.

These distributions are defined by their own characteristic functions. The bit-o-steg hiding distorts thatdistribution by randomly changes certain entries thus altering the function. Using the inner product, we could test for a matchbetween the characteristic function and the suspect image’s probability distribution. Unfortunately, the distribution functionsvary based on the subject of the picture. Furthermore, we lack the statistical background necessary to classify these distributionsand properly identify the characteristic functions. Thus, implementing bit-o-steg detection proved to be beyond the scope ofthis project.