Heterogeneous Malware Spread Process in Star Network

Title	Heterogeneous Malware Spread Process in Star Network
Publication Type	Conference Paper
Year of Publication	2017
Authors	Jiao, L., Yin, H., Guo, D., Lyu, Y.
Conference Name	2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW)
Date Published	jun
ISBN Number	978-1-5386-3292-5
Keywords	Analytical 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
Abstract	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.
URL	https://ieeexplore.ieee.org/document/7979827/
DOI	10.1109/ICDCSW.2017.35
Citation Key	jiao_heterogeneous_2017