Evolutionary virus immune strategy for temporal networks based on community vitality

Li, M; Fu, C; Liu, XY; Yang, J; Zhu, T; Han, L

Evolutionary virus immune strategy for temporal networks based on community vitality

Li, M Fu, C Liu, XY Yang, J Zhu, T

Han, L

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, 2017, 74, pp. 276-290
Issue Date:: 2017-09-01

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Field	Value	Language
dc.contributor.author	Li, M
dc.contributor.author	Fu, C
dc.contributor.author	Liu, XY
dc.contributor.author	Yang, J
dc.contributor.author	Zhu, T https://orcid.org/0000-0003-3411-7947
dc.contributor.author	Han, L
dc.date.accessioned	2022-08-15T05:42:27Z
dc.date.available	2022-08-15T05:42:27Z
dc.date.issued	2017-09-01
dc.identifier.citation	Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, 2017, 74, pp. 276-290
dc.identifier.issn	0167-739X
dc.identifier.issn	1872-7115
dc.identifier.uri	http://hdl.handle.net/10453/160214
dc.description.abstract	Preventing viruses spreading in networks is a hot topic. Existing immune strategies are mainly designed for static networks, which become ineffective for temporal networks. In this paper, we propose an evolutionary virus immune strategy for temporal networks, which takes into account the community evolution. First, we define a new metric, community vitality (CV), to quantize the evolution characteristics of communities. Second, based on the community vitality, we propose an immune strategy which selects an optimized number of initial nodes according to node influence (NI). Third, a theoretical analysis is proposed to measure the immune effect of the evolutionary immune strategy. Compared with the random immunization, the targeted immunization and the acquaintance immune strategy, we show that the proposed strategy has a much larger coverage, i.e., more nodes will have immune ability given the same number of initial immune nodes.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications
dc.relation.isbasedon	10.1016/j.future.2016.05.015
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0803 Computer Software, 0805 Distributed Computing, 0806 Information Systems
dc.subject.classification	Distributed Computing
dc.title	Evolutionary virus immune strategy for temporal networks based on community vitality
dc.type	Journal Article
utslib.citation.volume	74
utslib.for	0803 Computer Software
utslib.for	0805 Distributed Computing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-15T05:42:26Z
pubs.publication-status	Published
pubs.volume	74

Abstract:

Preventing viruses spreading in networks is a hot topic. Existing immune strategies are mainly designed for static networks, which become ineffective for temporal networks. In this paper, we propose an evolutionary virus immune strategy for temporal networks, which takes into account the community evolution. First, we define a new metric, community vitality (CV), to quantize the evolution characteristics of communities. Second, based on the community vitality, we propose an immune strategy which selects an optimized number of initial nodes according to node influence (NI). Third, a theoretical analysis is proposed to measure the immune effect of the evolutionary immune strategy. Compared with the random immunization, the targeted immunization and the acquaintance immune strategy, we show that the proposed strategy has a much larger coverage, i.e., more nodes will have immune ability given the same number of initial immune nodes.

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http://hdl.handle.net/10453/160214