CERIAS - Center for Education and Research in Information Assurance and Security

Skip Navigation
Purdue University - Discovery Park
Center for Education and Research in Information Assurance and Security

Architectural Considerations for Anomaly Detection

Wenke Lee - Georgia Tech

Feb 09, 2005

Size: 122.7MB

Download: Video Icon MP4 Video  
Watch in your Browser   Watch on Youtube Watch on YouTube


The most commonly used intrusion detection system (IDS) performance metrics are detection rate and false alarm rate. From a usability point of view, a very important measurement is Bayesian detection rate, which indicates how likely there is an intrusion when the IDS outputs an alert. It depends on detection rate, false alarm rate, and base rate (the prior probability of intrusion). Typically, an anomaly detection system has a low Bayesian detection rate because it has a non-zero false alarm rate and the base rate in the target environment is very low.

We argue that we need better system architecture to improve Bayesian detection rate. The main objective is to increase the base rate of data stream analyzed by complex detection modules. The general principle is to use layered architecture.

One approach is to use a cascade of successively more complex detection modules. We show that base rate increases from one layer to the next. In many cases, the overall false alarm rate of the cascade can be very low. We describe a worm detection system with cascade architecture. In DSC, the lower layer module identifies hosts with

Unless otherwise noted, the security seminar is held on Wednesdays at 4:30P.M. STEW G52 (Suite 050B), West Lafayette Campus. More information...


The views, opinions and assumptions expressed in these videos are those of the presenter and do not necessarily reflect the official policy or position of CERIAS or Purdue University. All content included in these videos, are the property of Purdue University, the presenter and/or the presenter’s organization, and protected by U.S. and international copyright laws. The collection, arrangement and assembly of all content in these videos and on the hosting website exclusive property of Purdue University. You may not copy, reproduce, distribute, publish, display, perform, modify, create derivative works, transmit, or in any other way exploit any part of copyrighted material without permission from CERIAS, Purdue University.