Hello IDS folks, I'm currently doing a mini-project involving applying machine learning techniques to the identification of hostile network traffic. My focus is on TCP traffic, and I'm looking at header and content based inspection. I'm wrapping up my feature extraction code now, whereby I've imported all TCP sessions from the DARPA training sets into a DB and have tagged the hostile sessions.
My question is, does anyone have any bright ideas of some useful, simple content analysis attributes? As it's a statistical/ML approach I'm trying to come up with as generic as possible ideas. So far I'm calculating things like session data entropy, most frequent character, counts of certain characters. I'm brand new to this field, but am really excited about this project. Any feedback/advice would be greatly appreciated. Thanks! G ----------------------------------------------------------------- Securing Your Online Data Transfer with SSL. A guide to understanding SSL certificates, how they operate and their application. By making use of an SSL certificate on your web server, you can securely collect sensitive information online, and increase business by giving your customers confidence that their transactions are safe. http://www.dinclinx.com/Redirect.aspx?36;5001;25;1371;0;1;946;9a80e04e1a17f194
