Immunization and targeted destruction of networks using explosive percolation

TL;DR

This paper introduces 'explosive immunization', a novel network immunization method that efficiently fragments networks by combining explosive percolation with a node scoring system, outperforming existing strategies especially on large networks.

Contribution

The paper presents a new explosive immunization technique that effectively and rapidly fragments networks, improving on prior methods by integrating explosive percolation with node scoring.

Findings

More efficient than existing strategies

Faster and scalable to large networks

Effective on real-world and model networks

Abstract

A new method (`explosive immunization' (EI)) is proposed for immunization and targeted destruction of networks. It combines the explosive percolation (EP) paradigm with the idea of maintaining a fragmented distribution of clusters. The ability of each node to block the spread of an infection (or to prevent the existence of a large cluster of connected nodes) is estimated by a score. The algorithm proceeds by first identifying low score nodes that should not be vaccinated/destroyed, analogously to the links selected in EP if they do not lead to large clusters. As in EP, this is done by selecting the worst node (weakest blocker) from a finite set of randomly chosen `candidates'. Tests on several real-world and model networks suggest that the method is more efficient and faster than any existing immunization strategy. Due to the latter property it can deal with very large networks.