Considering Quarantine in the SIRA Malware Propagation Model
As the beginning of the 21st century was marked by a strong development in data science and, consequently, in computer networks, models for designing preventive actions against intruding, data stealing, and destruction became mandatory. Following this line, several types of epidemiological models ha...
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doaj-b44d93ea5fa248668fa90a58a9ef59232020-11-25T03:24:52ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/64671046467104Considering Quarantine in the SIRA Malware Propagation ModelJosé Roberto C. Piqueira0Cristiane M. Batistela1Escola Politécnica da Universidade de São Paulo, Avenida Prof. Luciano Gualberto, Travessa 3, N. 158, 05508-900 São Paulo, SP, BrazilEscola Politécnica da Universidade de São Paulo, Avenida Prof. Luciano Gualberto, Travessa 3, N. 158, 05508-900 São Paulo, SP, BrazilAs the beginning of the 21st century was marked by a strong development in data science and, consequently, in computer networks, models for designing preventive actions against intruding, data stealing, and destruction became mandatory. Following this line, several types of epidemiological models have been developed and improved, considering different operational approaches. The development of the research line using traditional SIR(Susceptible, Infected, Removed) model for data networks started in the 1990s. In 2005, an epidemiological compartmental model containing antidotal nodes, SIRA (Susceptible, Infected, Removed, Antidotal), was introduced to study how the antivirus policies affect the network reliability. The idea here is to study the consequence of quarantine actions in a network by modifying the SIRA model, introducing quarantine nodes generating the SIQRA (Susceptible, Infected, Quarantine, Removed, Antidotal) model. Analytical and numerical approaches result in parameter conditions for the existence and stability of disease-free and endemic equilibrium points for two different cases: saturation and nonsaturation of the quarantine population block. Based on these results, operational actions can be planned to improve the network reliability.http://dx.doi.org/10.1155/2019/6467104 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
José Roberto C. Piqueira Cristiane M. Batistela |
spellingShingle |
José Roberto C. Piqueira Cristiane M. Batistela Considering Quarantine in the SIRA Malware Propagation Model Mathematical Problems in Engineering |
author_facet |
José Roberto C. Piqueira Cristiane M. Batistela |
author_sort |
José Roberto C. Piqueira |
title |
Considering Quarantine in the SIRA Malware Propagation Model |
title_short |
Considering Quarantine in the SIRA Malware Propagation Model |
title_full |
Considering Quarantine in the SIRA Malware Propagation Model |
title_fullStr |
Considering Quarantine in the SIRA Malware Propagation Model |
title_full_unstemmed |
Considering Quarantine in the SIRA Malware Propagation Model |
title_sort |
considering quarantine in the sira malware propagation model |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2019-01-01 |
description |
As the beginning of the 21st century was marked by a strong development in data science and, consequently, in computer networks, models for designing preventive actions against intruding, data stealing, and destruction became mandatory. Following this line, several types of epidemiological models have been developed and improved, considering different operational approaches. The development of the research line using traditional SIR(Susceptible, Infected, Removed) model for data networks started in the 1990s. In 2005, an epidemiological compartmental model containing antidotal nodes, SIRA (Susceptible, Infected, Removed, Antidotal), was introduced to study how the antivirus policies affect the network reliability. The idea here is to study the consequence of quarantine actions in a network by modifying the SIRA model, introducing quarantine nodes generating the SIQRA (Susceptible, Infected, Quarantine, Removed, Antidotal) model. Analytical and numerical approaches result in parameter conditions for the existence and stability of disease-free and endemic equilibrium points for two different cases: saturation and nonsaturation of the quarantine population block. Based on these results, operational actions can be planned to improve the network reliability. |
url |
http://dx.doi.org/10.1155/2019/6467104 |
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