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Influence of Removing Leaf Node Neighbors on Network Controllability.

Chengpei Wu1,2, Siyi Xu1,2, Zhuoran Yu1,2

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Network attackers can disrupt control by targeting leaf node neighbors. Protecting these low-degree nodes enhances network controllability robustness.

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Area of Science:

  • Network Science
  • Cybersecurity
  • Graph Theory

Background:

  • Understanding network controllability is crucial for both attackers seeking to cause damage and defenders aiming to enhance network robustness.
  • Developing effective attack strategies is essential for advancing research on network controllability and its resilience.

Purpose of the Study:

  • To propose a novel attack strategy, Leaf Node Neighbor-based Attack (LNNA), to disrupt the controllability of undirected networks.
  • To evaluate the effectiveness of the LNNA strategy through simulations on various network types.

Main Methods:

  • The LNNA strategy involves targeting the neighbors of leaf nodes.
  • If no leaf nodes exist, the strategy targets neighbors of high-degree nodes to create leaf nodes.
  • Simulations were conducted on both synthetic and real-world networks.

Main Results:

  • The proposed LNNA strategy effectively disrupts network controllability.
  • Removing neighbors of low-degree nodes (degree 1 or 2) significantly reduces network controllability robustness.
  • Simulations confirmed the strategy's effectiveness on diverse network structures.

Conclusions:

  • The LNNA strategy provides a method for attackers to compromise network control.
  • Protecting low-degree nodes and their neighbors is vital for improving network controllability robustness during construction.