Visible to the public Heterogeneous Malware Spread Process in Star Network

TitleHeterogeneous Malware Spread Process in Star Network
Publication TypeConference Paper
Year of Publication2017
AuthorsJiao, L., Yin, H., Guo, D., Lyu, Y.
Conference Name2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW)
Date Publishedjun
ISBN Number978-1-5386-3292-5
KeywordsAnalytical models, Artificial neural networks, Computational modeling, computer viruses, Curing, epidemic threshold, extended N-intertwined model, finite size graph, graph theory, heterogeneous malware spread process, heterogeneous SIS model, heterogeneous virus spread, Human Behavior, infected nodes, malware analysis, malware spread process, meta-stable state fraction, Metrics, network theory (graphs), privacy, pubcrawl, resilience, Resiliency, Silicon, simulation, SIS model, star network, steady state infection, Steady-state

The heterogeneous SIS model for virus spread in any finite size graph characterizes the influence of factors of SIS model and could be analyzed by the extended N-Intertwined model introduced in [1]. We specifically focus on the heterogeneous virus spread in the star network in this paper. The epidemic threshold and the average meta-stable state fraction of infected nodes are derived for virus spread in the star network. Our results illustrate the effect of the factors of SIS model on the steady state infection.

Citation Keyjiao_heterogeneous_2017