Back to Search
Start Over
A methodological framework for vulnerability analysis of interdependent infrastructure systems under deliberate attacks
- Source :
- Chaos, Solitons & Fractals. 117:21-29
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- In this paper, we give a methodological framework to analyze vulnerability of interdependent infrastructure systems under deliberate attacks. Meanwhile, the intelligence of attackers is considered and a method of critical attack area identification according to community detection is proposed as well. The Interdependent power and gas system in Wuhan, China is taken as the example. We determine the vulnerabilities of different critical areas in both independent and interdependent scenarios. In the meantime, percolation theory are utilized and different coupling strengths are considered to further analyze the vulnerabilities. It is found that the disruption of only a few vertices may lead to complete collapsing for some critical areas and the vulnerabilities increase when systems become interdependent. Therefore, greater protection should be given to critical areas of a network in order to reduce the vulnerabilities when deliberate attacks occur. The proposed method could help decision makers develop mitigation techniques and optimal protection strategies.
- Subjects :
- 021110 strategic, defence & security studies
Computer science
General Mathematics
Applied Mathematics
media_common.quotation_subject
0211 other engineering and technologies
Vulnerability
General Physics and Astronomy
Statistical and Nonlinear Physics
02 engineering and technology
01 natural sciences
Interdependence
Identification (information)
Risk analysis (engineering)
Order (exchange)
Vulnerability assessment
0103 physical sciences
010306 general physics
media_common
Subjects
Details
- ISSN :
- 09600779
- Volume :
- 117
- Database :
- OpenAIRE
- Journal :
- Chaos, Solitons & Fractals
- Accession number :
- edsair.doi...........90080d53ccac42b836fd707ffc381df2
- Full Text :
- https://doi.org/10.1016/j.chaos.2018.10.011