Distributed Worm Simulation with a Realistic Internet Model
Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation
Simulating non-scanning worms on peer-to-peer networks
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
A realistic simulation of internet-scale events
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
MAISim: mobile agent malware simulator
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
On capturing malware dynamics in mobile power-law networks
Proceedings of the 4th international conference on Security and privacy in communication netowrks
A hybrid model for worm simulations in a large network
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Tools for worm experimentation on the DETER testbed
International Journal of Communication Networks and Distributed Systems
Virtual playgrounds for worm behavior investigation
RAID'05 Proceedings of the 8th international conference on Recent Advances in Intrusion Detection
Implementation of an emulation environment for large scale network security experiments
ACC'11/MMACTEE'11 Proceedings of the 13th IASME/WSEAS international conference on Mathematical Methods and Computational Techniques in Electrical Engineering conference on Applied Computing
Agent-based simulation of cooperative defence against botnets
Concurrency and Computation: Practice & Experience
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Abstract modeling, such as using epidemic models, has been the general method of choice for understanding and analyzing the high-level effects of worms. However, high-fidelity models, such as packet-level models, are indispensable for moving beyond aggregate effects, to capture finer nuances and complexities associated with known and future worms in realistic network environments. Here, we first identify the spectrum of available alternatives for worm modeling, and classify them according to their scalability and fidelity. Among them, we focus on three high-fidelity methods for modeling worms, and study their effectiveness with respect to scalability. Employing these methods, we are then able to, respectively, achieve some of the largest packet-level simulations of worm models to date; implant and attack actual worm monitoring/defense installations inside large simulated networks; and identify a workaround for real-time requirement that fundamentally constrains worm modeling at the highest fidelity levels.