Edge-based modeling of computer virus contagion on a tripartite graph
Wei Pan and
Zhen Jin
Applied Mathematics and Computation, 2018, vol. 320, issue C, 282-291
Abstract:
As a typical computer virus, a file virus can parasitize in executable files and infect other files when the host files are executed. Due to the strong similarity between computer viruses and their biological counterparts, in this paper we adapt the epidemiologically compartmental models to study the computer virus contagion. To trace the transmission process of file viruses and determine effective control measures, we derive a pairwise mathematical model by taking account of edge-based contagions. By constructing a tripartite graph, we can determine the potential edges on which contagions take place. The sensitivity analysis for some parameters is performed, indicating that the contagion of file viruses can be effectively restrained by reducing the use of portable storage devices with computers which have not installed antivirus softwares or by reducing the transmission rate from infected web pages to susceptible computers. It is also found that the final number of infected computers is much lower in scale-free networks than in Poisson degree distributed networks.
Keywords: File virus; Edge-based contagion; Tripartite graph (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300317306720
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:320:y:2018:i:c:p:282-291
DOI: 10.1016/j.amc.2017.09.044
Access Statistics for this article
Applied Mathematics and Computation is currently edited by Theodore Simos
More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().