Model and estimation of worm propagation under network partition

Authors:
Ping Wang;Binxing Fang;Xiaochun Yun
Affiliations:
Dept. of Computer Science and Technology, Harbin Institute of Technology, Heilongjiang Harbin, China;Dept. of Computer Science and Technology, Harbin Institute of Technology, Heilongjiang Harbin, China;Dept. of Computer Science and Technology, Harbin Institute of Technology, Heilongjiang Harbin, China
Venue:
ISPEC'06 Proceedings of the Second international conference on Information Security Practice and Experience
Year:
2006

Citing 5
Cited 0

Code-Red: a case study on the spread and victims of an internet worm

Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
A Behavior-Based Anti-Worm System

AINA '03 Proceedings of the 17th International Conference on Advanced Information Networking and Applications
Inside the Slammer Worm

IEEE Security and Privacy
Monitoring and early warning for internet worms

Proceedings of the 10th ACM conference on Computer and communications security
Modeling the effects of timing parameters on virus propagation

Proceedings of the 2003 ACM workshop on Rapid malcode

Quantified Score

Hi-index	0.00

Visualization

Abstract

Several worm propagation models have been proposed to describe the behavior of worms in order to find the weak link in the worm propagation for the purpose of further treatment measures. In this paper, we investigate the relation between worm spread and the scale of network. The partition-based model of worm propagation is developed, in which we focus on two key factors: the subnet number of the network to be partitioned into and the time to perform partition. Using a combination of analytic modeling and simulations, we describe how each of these two factors impacts the dynamics of worm epidemic. Based on our simulation experiment results, we propose the network partitioning approach to deescalate network scale and thus restrict the worm propagation in large scale networks.