Detecting Android malware by extracting a static call graph and applying ML https://blog.acolyer.org/2017/03/09/mamadroid-detecting-android-malware-by-building-markov-chains-of-behavorial-models/ (impressive how high-level the CFG is)
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I've released difftastic 0.63! In this release:
* Better parsing of Elixir, LaTeX, Make, Nix, Rust and YAML
* Better detecting of text encoding, especially on Windows
* Prebuilt musl binaries, so you can run released binaries on older systems!
Individuals and interactions over processes and tools => Competence trumps process
Working software over comprehensive documentation => Minimize time from program launch to deployment of simplest useful functionality
I really like the DoD's phrasings of classic agile maxims:
Fascinating talk on applying deep learning to detecting cheaters in CS:GO https://www.youtube.com/watch?v=kTiP0zKF9bc
The presenter discusses how they get machine-readable data out of matches, and how they still keep a human in the loop (ML just feeds the human analysis component).