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Optimal control of joint multi-virus infection and information spreading. / Taynitskiy, Vladislav; Gubar, Elena; Fedyanin, Denis; Petrov, Ilya; Zhu, Quanyan.

In: IFAC-PapersOnLine, Vol. 53, No. 2, 2020, p. 6650-6655.

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Harvard

Taynitskiy, V, Gubar, E, Fedyanin, D, Petrov, I & Zhu, Q 2020, 'Optimal control of joint multi-virus infection and information spreading', IFAC-PapersOnLine, vol. 53, no. 2, pp. 6650-6655. https://doi.org/10.1016/j.ifacol.2020.12.086

APA

Vancouver

Author

Taynitskiy, Vladislav ; Gubar, Elena ; Fedyanin, Denis ; Petrov, Ilya ; Zhu, Quanyan. / Optimal control of joint multi-virus infection and information spreading. In: IFAC-PapersOnLine. 2020 ; Vol. 53, No. 2. pp. 6650-6655.

BibTeX

@article{e3d1fd9fd76b4cbb993dd1d52499a3f0,
title = "Optimal control of joint multi-virus infection and information spreading",
abstract = "Nowadays, epidemic models provide an appropriate tool to describe the propagation of biological viruses in human or animal populations, rumors and misinformation in social networks, and malware in both computer and ad hoc networks. It is common that there are multiple types of malware infecting a network of computing devices, and different messages can spread over the social network. Information spreading and virus propagation are interdependent processes. To capture their independencies, we integrate two epidemic models into one holistic framework, known as the modified Susceptible-Warned-Infected-Recovered-Susceptible (SWIRS) model. The first epidemic model describes the information spreading regarding the risk of malware attacks and possible preventive procedures. The second one describes the propagation of multiple viruses over the network of devices. To minimize the impact of the virus spreading and improve the protection of the networks, we consider an optimal control problem with two types of control strategies: information spreading among healthy nodes and the treatment of infected nodes. We obtain the structure of optimal control strategies and study the condition of epidemic outbreaks. The main results are extended to the case of the network of two connected clusters. Numerical examples are used to corroborate the theoretical findings.",
keywords = "Epidemic Process, Information Spreading, Network Security, Optimal Control",
author = "Vladislav Taynitskiy and Elena Gubar and Denis Fedyanin and Ilya Petrov and Quanyan Zhu",
note = "Publisher Copyright: Copyright {\textcopyright} 2020 The Authors. This is an open access article under the CC BY-NC-ND license Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 21st IFAC World Congress 2020 ; Conference date: 12-07-2020 Through 17-07-2020",
year = "2020",
doi = "10.1016/j.ifacol.2020.12.086",
language = "English",
volume = "53",
pages = "6650--6655",
journal = "IFAC-PapersOnLine",
issn = "2405-8963",
publisher = "Elsevier",
number = "2",

}

RIS

TY - JOUR

T1 - Optimal control of joint multi-virus infection and information spreading

AU - Taynitskiy, Vladislav

AU - Gubar, Elena

AU - Fedyanin, Denis

AU - Petrov, Ilya

AU - Zhu, Quanyan

N1 - Publisher Copyright: Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - Nowadays, epidemic models provide an appropriate tool to describe the propagation of biological viruses in human or animal populations, rumors and misinformation in social networks, and malware in both computer and ad hoc networks. It is common that there are multiple types of malware infecting a network of computing devices, and different messages can spread over the social network. Information spreading and virus propagation are interdependent processes. To capture their independencies, we integrate two epidemic models into one holistic framework, known as the modified Susceptible-Warned-Infected-Recovered-Susceptible (SWIRS) model. The first epidemic model describes the information spreading regarding the risk of malware attacks and possible preventive procedures. The second one describes the propagation of multiple viruses over the network of devices. To minimize the impact of the virus spreading and improve the protection of the networks, we consider an optimal control problem with two types of control strategies: information spreading among healthy nodes and the treatment of infected nodes. We obtain the structure of optimal control strategies and study the condition of epidemic outbreaks. The main results are extended to the case of the network of two connected clusters. Numerical examples are used to corroborate the theoretical findings.

AB - Nowadays, epidemic models provide an appropriate tool to describe the propagation of biological viruses in human or animal populations, rumors and misinformation in social networks, and malware in both computer and ad hoc networks. It is common that there are multiple types of malware infecting a network of computing devices, and different messages can spread over the social network. Information spreading and virus propagation are interdependent processes. To capture their independencies, we integrate two epidemic models into one holistic framework, known as the modified Susceptible-Warned-Infected-Recovered-Susceptible (SWIRS) model. The first epidemic model describes the information spreading regarding the risk of malware attacks and possible preventive procedures. The second one describes the propagation of multiple viruses over the network of devices. To minimize the impact of the virus spreading and improve the protection of the networks, we consider an optimal control problem with two types of control strategies: information spreading among healthy nodes and the treatment of infected nodes. We obtain the structure of optimal control strategies and study the condition of epidemic outbreaks. The main results are extended to the case of the network of two connected clusters. Numerical examples are used to corroborate the theoretical findings.

KW - Epidemic Process

KW - Information Spreading

KW - Network Security

KW - Optimal Control

UR - http://www.scopus.com/inward/record.url?scp=85105037732&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2020.12.086

DO - 10.1016/j.ifacol.2020.12.086

M3 - Conference article

AN - SCOPUS:85105037732

VL - 53

SP - 6650

EP - 6655

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 2

T2 - 21st IFAC World Congress 2020

Y2 - 12 July 2020 through 17 July 2020

ER -

ID: 78139484