Research output: Contribution to journal › Conference article › peer-review
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.Research output: Contribution to journal › Conference article › peer-review
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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