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Weekly Report -22/09/13




Still working on the tEntropy detector, but have made good progress this week. Ironed out any bugs that I found, and have output in the correct format. Then, I spent a great deal of time collecting output for 8 different streams, each with different character bin sizes and string lengths. Also wrote a python script which takes the output files for different streams (which includes the string used for entropy measurements) and passes it to an external script which calculates an average t-entropy measurement for each timestamp. So, I now have a bunch of output files with entropy values that need to be plotted to determine which combination of string lengths and character bin sizes would be most optimal.

After a brief look at a couple of graphs, it seemed that a greater string length(50) had no benefits over using a smaller string size (20). The patterns were practically similar for each string length and differed very little, which implies that the additional computational cost of calculating the t-entropy for 50characters for every single timestamp is not worth it.