Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Multiscale vulnerability of complex networks.

Stefano Boccaletti1, Javier Buldú, Regino Criado

  • 1Embassy of Italy in Tel Aviv, 25 Hamered Street, 68125 Tel Aviv, Israel.

Chaos (Woodbury, N.Y.)
|January 1, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Perspectives on Robustness and Resilience of Complex Networks.

Entropy (Basel, Switzerland)·2026
Same author

Matrix-based pagerank control in hypergraphs for semantic text summaries.

Scientific reports·2025
Same author

Modeling the Spread of Misfolded Proteins in Alzheimer's Disease using Higher-Order Simplicial Complex Contagion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

The networks of ingredient combinations as culinary fingerprints of world cuisines.

NPJ science of food·2025
Same author

Solitary states in spiking oscillators with higher-order interactions.

Physical review. E·2025
Same author

Privacy preserving optimization of communication networks.

Nature communications·2025
Same journal

Topological dependence of viral mutation spread in complex host-interaction networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multifractal signatures of Hamiltonian chaos in Hyperion's rotational dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
Same journal

State estimation in spatiotemporal chaos via low-rank StatFEM.

Chaos (Woodbury, N.Y.)·2026
Same journal

Universal response functions in driven dissipative tunneling dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

A network-based approach to characterize the dynamics of the coupling field of thermoacoustic oscillators in annular geometry.

Chaos (Woodbury, N.Y.)·2026
See all related articles

We developed a new method to measure complex network vulnerability to damage. This approach uses link betweenness to better assess network resilience against attacks and failures.

Area of Science:

  • Network science
  • Graph theory
  • Systems engineering

Background:

  • Complex networks are susceptible to functional degradation from random damages or malicious attacks.
  • Quantifying network vulnerability is crucial for robust network design and maintenance.
  • Existing vulnerability measures may not adequately capture the nuances of complex network behavior.

Purpose of the Study:

  • To introduce a novel, multiscale approach for quantifying the vulnerability of complex networks.
  • To provide a more accurate measure of a network's capacity to maintain function under duress.
  • To address limitations of previous vulnerability assessment methods.

Main Methods:

  • Development of a new vulnerability quantification measure.
  • Utilizing combined powers of link betweenness for multiscale evaluation.

Related Experiment Videos

  • Testing the proposed method against various network scenarios.
  • Main Results:

    • The proposed measure effectively quantifies network vulnerability on multiple scales.
    • The new approach demonstrates superior performance in specific cases where older methods falter.
    • Validation of the method's ability to describe network resilience accurately.

    Conclusions:

    • The novel multiscale vulnerability measure offers a significant advancement in network analysis.
    • This method provides a more comprehensive understanding of network resilience.
    • Applications include improved design and protection strategies for technological networks.