Routing in the Internet
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Introduction to Algorithms
Code red worm propagation modeling and analysis
Proceedings of the 9th ACM conference on Computer and communications security
IEEE Security and Privacy
Simulating realistic network worm traffic for worm warning system design and testing
Proceedings of the 2003 ACM workshop on Rapid malcode
Measuring ISP topologies with rocketfuel
IEEE/ACM Transactions on Networking (TON)
Defense and Detection Strategies against Internet Worms
Defense and Detection Strategies against Internet Worms
Discrete event fluid modeling of background TCP traffic
ACM Transactions on Modeling and Computer Simulation (TOMACS)
The monitoring and early detection of internet worms
IEEE/ACM Transactions on Networking (TON)
On the performance of internet worm scanning strategies
Performance Evaluation
The impact of stochastic variance on worm propagation and detection
Proceedings of the 4th ACM workshop on Recurring malcode
Spatial-temporal modeling of malware propagation in networks
IEEE Transactions on Neural Networks
Simulating network cyber attacks using splitting techniques
Proceedings of the Winter Simulation Conference
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Simulation of Internet worms (and other malware) requires tremendous computing resources when every packet generated by the phenomena is modeled individually; on the other hand, models of worm growth based on differential equations lack the significant variability inherent in worms that sample targets randomly. This article addresses the problem with a model that focuses on times of infection. We propose a hybrid discrete-continuous model that minimizes execution time subject to an accuracy constraint on variance. We also develop an efficiently executed model of preferential random scanning and use it to investigate the sensitivity of worm propagation speed to the distribution of susceptible hosts through the network, and to the local preference probability. Finally, we propose and study two optimizations to a fluid-based simulation of scan traffic through a backbone network, observing an order-of-magnitude improvement in execution speed.