The role of link redundancy and structural heterogeneity in network disintegration

While link redundancy has long been acknowledged as a critical factor in network robustness, current approaches frequently neglect the inherent heterogeneity of structure, thereby falling short of optimal network disintegration. This study introduces the novel Neighborhood Dissimilarity Community Heterogeneity (NDCH) framework, which systematically investigates redundancy elimination from a new perspective of neighborhood dissimilarity, while concurrently integrating structural heterogeneity derived from community structure. Extensive experiments on both synthetic and diverse real-world networks reveal that strategies developed under NDCH framework markedly outperform existing state-of-the-art methods in network disintegration, with performance improvements reaching up to 60.151 % and 31.000 % for Schneider R and the critical removal fraction fc, respectively. Notably, additional analysis consistently indicates low correlations (Kendall's Tau < 0.6) and distinct value distributions between NDCH-based strategies and the state-of-the-art approaches. In summary, the novel framework underscores the significance of both redundancy and structural heterogeneity when devising network disintegration strategies, offering a substantial leap forward in enhancing network robustness against malicious attacks and various disruptions, especially in infrastructure networks