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The European Physical Journal Special Topics

, Volume 223, Issue 11, pp 2087–2106 | Cite as

Vulnerability of network of networks

Review
Part of the following topical collections:
  1. Dynamic Systems: From Statistical Mechanics to Engineering Applications

Abstract

Our dependence on networks – be they infrastructure, economic, social or others – leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on – Internet, mobile phone, transportation, air travel, banking, etc. – emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.

Keywords

European Physical Journal Special Topic Order Phase Transition Percolation Theory Giant Component Single Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© EDP Sciences and Springer 2014

Authors and Affiliations

  1. 1.Department of PhysicsBar-Ilan UniversityRamat GanIsrael
  2. 2.Center for Polymer Studies and Department of Physics, Boston UniversityBostonUSA
  3. 3.Channing Division of Network Medicine, Brigham and Women’s Hospital, and Harvard Medical SchoolBostonUSA
  4. 4.Department of AutomationShanghai Jiao Tong, UniversityShanghaiP.R. China
  5. 5.Center for Complex Network Research and Department of Physics, Northeastern UniversityBostonUSA

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