IEICE TRANSACTIONS on Information
Study on Network Vulnerability Identification and Equilibrated Network Immunization Strategy
Summary :
Network structure has a great impact both on hazard spread and network immunization. The vulnerability of the network node is associated with each other, assortative or disassortative. Firstly, an algorithm for vulnerability relevance clustering is proposed to show that the vulnerability community phenomenon is obviously existent in complex networks. On this basis, next, a new indicator called network “hyper-betweenness” is given for evaluating the vulnerability of network node. Network hyper-betweenness can reflect the importance of network node in hazard spread better. Finally, the dynamic stochastic process of hazard spread is simulated based on Monte-Carlo sampling method and a two-player, non-cooperative, constant-sum game model is designed to obtain an equilibrated network immunization strategy.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.1 pp.46-55
- Publication Date
- 2012/01/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.46
- Type of Manuscript
- Special Section PAPER (Special Section on Trust, Security and Privacy in Computing and Communication Systems)
- Category
- Trust
Authors
Keyword
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Chi GUO, Li-na WANG, Xiao-ying ZHANG, "Study on Network Vulnerability Identification and Equilibrated Network Immunization Strategy" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 1, pp. 46-55, January 2012, doi: 10.1587/transinf.E95.D.46.
Abstract: Network structure has a great impact both on hazard spread and network immunization. The vulnerability of the network node is associated with each other, assortative or disassortative. Firstly, an algorithm for vulnerability relevance clustering is proposed to show that the vulnerability community phenomenon is obviously existent in complex networks. On this basis, next, a new indicator called network “hyper-betweenness” is given for evaluating the vulnerability of network node. Network hyper-betweenness can reflect the importance of network node in hazard spread better. Finally, the dynamic stochastic process of hazard spread is simulated based on Monte-Carlo sampling method and a two-player, non-cooperative, constant-sum game model is designed to obtain an equilibrated network immunization strategy.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.46/_p
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@ARTICLE{e95-d_1_46,
author={Chi GUO, Li-na WANG, Xiao-ying ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Study on Network Vulnerability Identification and Equilibrated Network Immunization Strategy},
year={2012},
volume={E95-D},
number={1},
pages={46-55},
abstract={Network structure has a great impact both on hazard spread and network immunization. The vulnerability of the network node is associated with each other, assortative or disassortative. Firstly, an algorithm for vulnerability relevance clustering is proposed to show that the vulnerability community phenomenon is obviously existent in complex networks. On this basis, next, a new indicator called network “hyper-betweenness” is given for evaluating the vulnerability of network node. Network hyper-betweenness can reflect the importance of network node in hazard spread better. Finally, the dynamic stochastic process of hazard spread is simulated based on Monte-Carlo sampling method and a two-player, non-cooperative, constant-sum game model is designed to obtain an equilibrated network immunization strategy.},
keywords={},
doi={10.1587/transinf.E95.D.46},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - Study on Network Vulnerability Identification and Equilibrated Network Immunization Strategy
T2 - IEICE TRANSACTIONS on Information
SP - 46
EP - 55
AU - Chi GUO
AU - Li-na WANG
AU - Xiao-ying ZHANG
PY - 2012
DO - 10.1587/transinf.E95.D.46
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2012
AB - Network structure has a great impact both on hazard spread and network immunization. The vulnerability of the network node is associated with each other, assortative or disassortative. Firstly, an algorithm for vulnerability relevance clustering is proposed to show that the vulnerability community phenomenon is obviously existent in complex networks. On this basis, next, a new indicator called network “hyper-betweenness” is given for evaluating the vulnerability of network node. Network hyper-betweenness can reflect the importance of network node in hazard spread better. Finally, the dynamic stochastic process of hazard spread is simulated based on Monte-Carlo sampling method and a two-player, non-cooperative, constant-sum game model is designed to obtain an equilibrated network immunization strategy.
ER -
English
