Generalized k-cores of networks under attack with limited knowledge

Shang, Yilun (2021) Generalized k-cores of networks under attack with limited knowledge. Chaos, Solitons & Fractals, 152. p. 111305. ISSN 0960-0779

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Official URL: https://doi.org/10.1016/j.chaos.2021.111305

Abstract

Network theory has been used as an effective approach for understanding and controlling many real-world large-scale systems. A significant aspect of network operation is its robustness against failures and attacks. Here, we develop a theoretical framework for two classes of network attack with limited knowledge, namely, min-n and max-n attacks, where only n nodes are observed and a node with smallest or largest degree is removed at a time until a fraction 1 − p of nodes are attacked. We study the effect of these attacks on the generalized k-core (Gk-core) of the network, which is obtained by implementing a k-leaf pruning process, removing progressively nodes with degree smaller than k alongside their nearest neighbors. This removal process can be viewed as a generation of the ordinary k-core decomposition. It is found that the G2-core undergoes a continuous phase transition with respect to p while Gk-core shows a first-order percolation transition for k ≥ 3 under both types of attacks for all n. We reveal that knowing one more node during attacks, improving from n = 1 to n = 2, turns out to be most beneficial in terms of changing the robustness of Gk-core in both directions. Moreover, it is shown that degree heterogeneity plays a role in robustness as prioritizing attack on small-degree nodes in heterogeneous networks may help consolidate the Gk-core, but also in stability where hub nodes act like anchors stabilizing the Gk-core structure. Our results offer insight into the design of resilient complex systems and evaluation of network robustness and stability.

Item Type: Article
Uncontrolled Keywords: Network, core, percolation, attack, robustness, stability
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 13 Aug 2021 10:31
Last Modified: 24 Aug 2021 16:30
URI: http://nrl.northumbria.ac.uk/id/eprint/46911

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