CCS2011: Enemy of the Good
ToDo
- Gather data from different IDS observables to show they aren't Gaussian
- system calls (Luc)
- network traffic
- log files
- Machine learning
- standard machine learning methods approximate distributions
- approximation works best if Gaussian but has limits (show mathematically)
- non-Gaussian distributions place much harsher restrictions on error rates, they don't go down proportionally to sample size? (more math)
- Survey of results in IDS literature
Title
The Enemy of the Good: Re-evaluating Research Directions in Intrusion Detection