Unrelated background information:
I wished I'd gotten a lot further a
lot sooner with this. Also this blog post is only barely up to the standard I
set for myself. Compressing so much statistics and machine learning into a blog
post of reasonable length while avoiding excessive math is a terribly difficult
thing to do. I hope that it lifts the vail a bit around what machine learning
is and how it can be leveraged in a malware setting, but if you really wish to
get down with it there can be no two opinions about you need a real text book
with all the rigor that it requires.
Finally it took a long time because most of my
family conspired to celebrate round birthdays. Also climbing season started
which keeps me away from the computer. Finally I have this feeling that the
"Predator" from Machine Learning Part 1. blog produced insufficient
amount of features. So spend a significant amount of time embedding my code
emulator (from unpacking with primitive emulation) into Predator at first
thinking it would be easy. Emulating on 80000 files malformed files, where a
significant amount is missing DLL's etc. turned out to be way more time
consuming than I imagined.
The blog post is here:
Machine learning with malware part 2: Model Selection
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