Robustness of Random Networks with Selective Reinforcement against Attacks

Autor:	Kawasumi, Tomoyo, Hasegawa, Takehisa
Rok vydání:	2024
Předmět:	Physics - Physics and Society
Zdroj:	Physica A: Statistical Mechanics and its Applications, Volume 649 (2024) 129958
Druh dokumentu:	Working Paper
DOI:	10.1016/j.physa.2024.129958
Popis:	We investigate the robustness of random networks reinforced by adding hidden edges against targeted attacks. This study focuses on two types of reinforcement: uniform reinforcement, where edges are randomly added to all nodes, and selective reinforcement, where edges are randomly added only to the minimum degree nodes of the given network. We use generating functions to derive the giant component size and the critical threshold for the targeted attacks on reinforced networks. Applying our analysis and Monte Carlo simulations to the targeted attacks on scale-free networks, it becomes clear that selective reinforcement significantly improves the robustness of networks against the targeted attacks. Comment: 16 pages, 6 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.08535 Zobrazit plný text záznamu View this record from Arxiv