Getting Started with Machine Learning for Incident Detection presented at bsidesboston 2016

by David J. Bianco, Chris Mccubbin,

Summary : Organizations today are collecting more information about what's going on in their environments than ever before, but manually sifting through all this data to find evil on your network is next to impossible. Increasingly, companies are turning to big data analytics and machine learning to detect security incidents. Most of these solutions are black-box products that cannot be easily tailored to the environments in which they run. Therefore, reliable detection of security incidents remains elusive, and there is a distinct lack of open source innovation.
It doesn't have to be this way! Many security pros think nothing of whipping up a script to extract downloaded files from a PCAP, yet recoil in horror at the idea of writing their own machine learning tools. The "analytics barrier" is perceived to be very high, but getting started is much easier than you think!
In this presentation, we’ll walk through the creation of a simple Python script that can learn to find malicious activity in your HTTP proxy logs. At the end of it all, you'll not only gain a useful tool to help you identify things that your IDS and SIEM might have missed, but you’ll also have the knowledge necessary to adapt that code to other uses as well.