Generating representative Web workloads for network and server performance evaluation
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Computing in Science and Engineering
An Empirical Model of HTTP Network Traffic
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
The Georgia Tech Network Simulator
MoMeTools '03 Proceedings of the ACM SIGCOMM workshop on Models, methods and tools for reproducible network research
Simulating realistic network worm traffic for worm warning system design and testing
Proceedings of the 2003 ACM workshop on Rapid malcode
Worm propagation modeling and analysis under dynamic quarantine defense
Proceedings of the 2003 ACM workshop on Rapid malcode
Generating realistic workloads for network intrusion detection systems
WOSP '04 Proceedings of the 4th international workshop on Software and performance
Polygraph: Automatically Generating Signatures for Polymorphic Worms
SP '05 Proceedings of the 2005 IEEE Symposium on Security and Privacy
Creating models of internet background traffic suitable for use in evaluating network intrusion detection systems
Autograph: toward automated, distributed worm signature detection
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Modeling malcode with Hephaestus: beyond simple spread
ACM-SE 45 Proceedings of the 45th annual southeast regional conference
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Although the most basic simulations of worm spread require the simulation of only the traffic generated by the malcode, when modeling the effects of antiworm techniques the results can be misleading if the background traffic is not taken into consideration. Despite the need for background traffic, no anti-worm simulation to date incorporates general traffic in the model.In this work I introduce a simple model of background traffic generation for arbitrary size networks. My approach builds on a traffic generation model for security testing and is validated against the predictions of the base model.