A New Virus Source Inference Model Based on Network Performance Estimation

• Published in: Applied Mechanics and Materials Vol. 433-435; no. Advances in Mechatronics and Control Engineering II; pp. 1693 - 1698
• Main Authors: Zhu, Hai Ting, Ding, Wei, Ni, Jun Hui
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 01.10.2013
• Subjects: Algorithms; Computer simulation; Estimators; Graph theory; Inference; Networks; Performance measurement; Tomography; Topology; Viruses; Network Performance Estimation; Network Tomography; Virus Source Inference; Rumor Centrality
• ISBN: 303785894X; 9783037858943
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.433-435.1693

Combining network tomography, a new virus source inference model based on network performance is proposed. Both the topology information and real time network status are considered in our model. Performance metrics are introduced into rumor-centrality-based source detecting algorithm in an active inference way. By improving the process of setting up the spanning tree of infected topology we raise the virus source inference precision and reduce the time complexity of rumor-centrality-based algorithm from O(N2(|V|+|E|)) to O(N2). The simulation results show that our model achieves better estimation accuracy than the algorithm using rumor center as the estimator.