Modeling Traffic Flow Using Conversation Exchange Dynamics for Identifying Network Attacks

We present a novel approach to identifying anomalous network events Specifically, a method for characterizing and displaying the flow of conversations across a distributed system with a high number of interacting entities is discussed and analyzed. Results from from attacks contained in the DARPA Lincoln Lab IDS test data and from operational network traffic are presented. These results suggest that our approach presents a unique perspective on anomalies in computer network traffic.