Percolation of localized attack on complex networks

TL;DR

This paper introduces a percolation framework to analyze the robustness of various complex networks against localized attacks, which target neighboring nodes, providing insights for improving network security and resilience.

Contribution

It develops an analytical and numerical framework for studying network robustness under localized attacks across different network types.

Findings

Localized attacks significantly reduce network connectivity.

Robustness varies with network topology and attack size.

Framework aids in designing more resilient networks.

Abstract

The robustness of complex networks against node failure and malicious attack has been of interest for decades, while most of the research has focused on random attack or hub-targeted attack. In many real-world scenarios, however, attacks are neither random nor hub-targeted, but localized, where a group of neighboring nodes in a network are attacked and fail. In this paper we develop a percolation framework to analytically and numerically study the robustness of complex networks against such localized attack. In particular, we investigate this robustness in Erd\H{o}s-R\'{e}nyi networks, random-regular networks, and scale-free networks. Our results provide insight into how to better protect networks, enhance cybersecurity, and facilitate the design of more robust infrastructures.