By by Martin Karresand.
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This explains the differences in the results for the 2-gram algorithm, which is especially good at utilising fixed parameters that are required by a file type. 19. The 2-gram algorithm is the best and is accompanied by three clusters at 85% detection rate. The clusters are, from left to right: 1. 1% false positives. 2. BFD and RoC combinations, the signed difference valued slightly to the right, 2% false positives. 3. RoC, 7% false positives. 4. BFD, 10% false positives. 19, the 2-gram algorithm is the first to reach a 100% detection rate, with a false positives rate of 86%.
When the similarity between a sample fragment and a centroid is measured the same type of quadratic distance metric as for the 1-gram file type categorisation method is used. 2) describes the metric, where matrix S depicts the sample 2-gram frequency distribution and C the mean value matrix of the 21 CHAPTER 2. exe). The Z-axis is plotted with a logarithmic scale and the frequency values are scaled down to correspond to 4 KiB of data. centroid. The standard deviation of 2-gram i j is represented by σi j .
We therefore have to include fragments ending in 0xFF and fragments starting with 0xD0 to 0xD7, and 0x00. The amount of extra fragment pairs to check after such an inclusion is manageable. Using a requirement of a correct RST marker sequence our test image gives us 18012 possible fragment pairs. 190 of the pairs are correct and can be joined together into a full image. The set of fragment pairs includes pairs where the joint cuts through a marker. The method of using correct RST markers sequences cannot give the fragment joint validity, thus we have to test every possible combination to find the correct one.