Computer Sciences Dept.

Toward Comprehensive Traffic Generation for Online IDS Evaluation

Joel Sommers, Vinod Yegneswaran, Paul Barford

We describe a traffic generation framework for conducting online evaluations of network intrusion detection systems over a wide range of realistic conditions. The framework integrates both benign and malicious traffic, enabling generation of IP packet streams with diverse characteristics from the perspective of {\em (i) packet content} (both header and payload), {\em (ii) packet mix} (order of packets in streams) and {\em (iii) packet volume} (arrival rate of packets in streams). We begin by describing a methodology for defining trust which forms the basis of our method for systematic extraction of ``benign'' traffic from live streams. We then detail how we combine these traces with application-specific automata to generate benign traffic streams. Next, we describe a methodology for malicious traffic generation, and techniques for integration with benign traffic to produce a range of realistic workload compositions. We realize our traffic generation framework in a tool we call Trident, and demonstrate its utility through a series of laboratory-based experiments using traces collected from our departmental border router, DARPA Intrusion Detection Evaluation data sets provided by Lincoln Lab, and a suite of malicious traffic modules that reproduce a broad range of attacks commonly seen in today's networks. Our experiments demonstrate the effects of varying packet content, mix, and volume on the performance of intrusion detection systems.

Download this report (PDF)

Return to tech report index

Computer Science | UW Home