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Core identification and attack strategies against regenerative complex networks
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Guo, Weisi and Lu, X. (2016) Core identification and attack strategies against regenerative complex networks. Electronic Letters, 52 (6). pp. 450-452. doi:10.1049/el.2015.3788 ISSN 0013-5194.
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Official URL: http://doi.org/10.1049/el.2015.3788
Abstract
Modelling enemy networks in a way that reveals their key entities and links is important when disrupting complex networks with high redundancy. In this paper, we examine how best to attack such networks under a limited ground intelligence constraint. The key modelling contribution is to include both the heterogeneity of the node functions and the dynamics of recuperation after destruction. Through identifying the core nodes, the results show that ground intelligence should focus on locating and attacking high degree nodes, yielding a 41% reduction in conflict length over random opportunistic targeting and a 23% reduction over specialist targeting. Even when difficult to replace specialists are considered, targeting high degree nodes that can recuperate quickly, remains the most effective method of attack. The impact is to allow military forces to more effectively target enemy nodes that will cause functional paralysis and create further collapses.
Item Type: | Journal Article | ||||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering U Military Science > U Military Science (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||||
Library of Congress Subject Headings (LCSH): | Artificial intelligence -- Military applications, Electronic countermeasures -- Networks, Computer, Cyberspace operations (Military science), Computers -- Military aspects | ||||||||
Journal or Publication Title: | Electronic Letters | ||||||||
Publisher: | IET | ||||||||
ISSN: | 0013-5194 | ||||||||
Official Date: | 17 March 2016 | ||||||||
Dates: |
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Volume: | 52 | ||||||||
Number: | 6 | ||||||||
Page Range: | pp. 450-452 | ||||||||
DOI: | 10.1049/el.2015.3788 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Copyright Holders: | IET, IEEE | ||||||||
Date of first compliant deposit: | 14 January 2016 | ||||||||
Date of first compliant Open Access: | 14 January 2016 | ||||||||
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