Impact of seed node position on network robustness under localized attacks

2026-02-06

AI Summary

This study addresses a critical limitation in existing research on network robustness, which typically assumes randomly distributed seed nodes and overlooks the pivotal role of their structural positions under localized attacks. To bridge this gap, the authors propose the Localized Attack Vulnerability Index (LAVI), a novel node-level metric that quantifies the cumulative link disruption triggered by a localized attack originating from a specific node, thereby assessing its destructive potential. By integrating topological analysis with numerical simulations, LAVI is systematically computed across diverse synthetic and real-world networks and benchmarked against classical centrality measures—degree, closeness, and betweenness. Results demonstrate that LAVI significantly outperforms these traditional metrics in predicting robustness degradation under localized attacks, exhibiting stronger correlation and generalizability, and highlighting their inherent inability to capture the spatial propagation dynamics characteristic of such attacks.

Technology Category

• Search and Optimization: Local Search
• Computer Vision: Adversarial Attacks & Robustness
• Natural Language Processing: Safety and Robustness

Application Category

• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

Localized attacks (LAs), where damage propagates from a single seed node to its neighbors, pose significant threats to the robustness of complex networks. Although previous studies have extensively analyzed network vulnerability under such attacks, they typically assume random seed node placement and evaluate average robustness. However, the structural position of the seed node can significantly impact the extent of damage. This study proposes the Localized Attack Vulnerability Index (LAVI), a node-level metric that quantifies the potential impact of a LA initiated at a specific node. LAVI quantifies the cumulative number of severed links during attack progression, capturing how local connectivity and topological position amplify the resulting damage. Numerical experiments on synthetic and real-world networks demonstrate that LAVI correlates more strongly with network robustness degradation than standard centrality measures, such as degree, closeness, and betweenness. Our findings highlight that classical centrality metrics fail to capture key dynamics of spatially localized failures, while LAVI provides an accurate and generalizable indicator of node vulnerability under such disruptions.

Problem

• localized attacks
• network robustness
• seed node position
• structural vulnerability
• complex networks

Innovation

• Localized Attack Vulnerability Index
• network robustness
• seed node position
• topological vulnerability
• centrality measures