Resilience of networks of multi-stable chaotic systems to targetted attacks

TL;DR

This paper studies how networks of multi-stable chaotic oscillators respond to targeted attacks, revealing that nodes with high centrality, especially betweeness, are critical for maintaining collective dynamics and resilience.

Contribution

It introduces a variant of multi-node Basin Stability to assess network resilience and demonstrates the critical role of high-centrality nodes in the robustness of chaotic oscillator networks.

Findings

Targeted attacks on high-centrality nodes can destroy network dynamics more efficiently than random attacks.

Hub nodes in star networks are crucial; perturbing them can collapse the entire system.

Betweeness centrality is the most influential factor in network vulnerability.

Abstract

We investigate the collective dynamics of chaotic multi-stable Duffing oscillators connected in different network topologies, ranging from star and ring networks, to scale-free networks. We estimate the resilience of such networks by introducing a variant of the concept of multi-node Basin Stability, which allows us to gauge the global stability of the collective dynamics of the network in response to large perturbations localized on certain nodes. We observe that in a star network, perturbing just the hub node has the capacity to destroy the collective state of the entire system. On the other hand, even when a majority of the peripheral nodes are strongly perturbed, the hub manages to restore the system to its original state. This demonstrates the drastic effect of the centrality of the perturbed node on the collective dynamics of the full network. Further, we explore scale-free networks of such multi-stable oscillators and demonstrate that targetted attacks on nodes with high centrality can destroy the collective dynamics much more efficiently than random attacks, irrespective of the nature of the nodal dynamics and type of perturbation. We also find clear evidence that the betweeness centrality of the perturbed node is most crucial for dynamical robustness, with the entire system being more vulnerable to attacks on nodes with high betweeness. These results are crucial for deciding which nodes to stringently safeguard in order to ensure the recovery of the network after targetted localized attacks.