A critical point for random graphs with a given degree sequence
Random Graphs 93 Proceedings of the sixth international seminar on Random graphs and probabilistic methods in combinatorics and computer science
On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Throttling Viruses: Restricting propagation to defeat malicious mobile code
ACSAC '02 Proceedings of the 18th Annual Computer Security Applications Conference
Proceedings of the 2003 ACM workshop on Rapid malcode
The Size of the Giant Component of a Random Graph with a Given Degree Sequence
Combinatorics, Probability and Computing
The Diameter of a Scale-Free Random Graph
Combinatorica
Vigilante: end-to-end containment of internet worms
Proceedings of the twentieth ACM symposium on Operating systems principles
Improving sensor network immunity under worm attacks: a software diversity approach
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Decentralized detector generation in cooperative intrusion detection systems
SSS'07 Proceedings of the 9h international conference on Stabilization, safety, and security of distributed systems
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We study how the spread of computer viruses, worms, and other self-replicating malware is affected by the logical topology of the network over which they propagate. We consider a model in which each host can be in one of 3 possible states - susceptible, infected or removed (cured, and no longer susceptible to infection). We characterise how the size of the population that eventually becomes infected depends on the network topology. Specifically, we show that if the ratio of cure to infection rates is larger than the spectral radius of the graph, and the initial infected population is small, then the final infected population is also small in a sense that can be made precise. Conversely, if this ratio is smaller than the spectral radius, then we show in some graph models of practical interest (including power law random graphs) that the final infected population is large. These results yield insights into what the critical parameters are in determining virus spread in networks.A category with the (minimum) three required fields