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Hierarchy measurement for modeling network dynamics under directed attacks.

M Rubinson1, N Levit-Binnun2, A Peled3,4

  • 1Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot, Israel.

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Summary
This summary is machine-generated.

Network resilience against targeted attacks can be predicted by initial connectivity. A novel "hierarchy" function approximates node removal order, revealing insights into complex system dynamics.

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Area of Science:

  • Complex systems science
  • Network science
  • Graph theory

Background:

  • Understanding network resilience to targeted attacks is crucial for complex systems.
  • Previous research often focused on global network properties, neglecting local dynamics.

Purpose of the Study:

  • To explore the local dynamics of network attack processes.
  • To predict dynamic network responses based on initial connectivity.
  • To introduce a novel nodal measurement for network dynamics.

Main Methods:

  • Investigated the order of node removal based on maximal degree.
  • Performed numerical demonstrations of network decay.
  • Introduced and analyzed the network "hierarchy" function (h).
  • Related attack dynamics exponents to spreading activation dynamics.

Main Results:

  • Maximal network degree M(τ) decays exponentially with time step τ, with a topology-dependent exponent.
  • The node removal order can be approximated using the hierarchy function h.
  • Identified exponents linking attack dynamics to spreading activation.

Conclusions:

  • Network attack dynamics and resilience can be predicted from initial graph connectivity.
  • The hierarchy function h is a novel and effective nodal measurement for network dynamics and structure.
  • Findings offer insights into both network robustness and information propagation.