Open Access

ARTICLE

A Low-Cost Network Topology Obfuscation Method for Critical Node Protection

Yanming Chen¹, Fuxiang Yuan^2,*, Zekang Wang²

1 School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, China
2 Key Laboratory of Cyberspace Situation Awareness of Henan Province, Zhengzhou, China

* Corresponding Author: Fuxiang Yuan. Email:

(This article belongs to the Special Issue: Cyberspace Mapping and Anti-Mapping Techniques)

Computers, Materials & Continua 2026, 87(2), 52 https://doi.org/10.32604/cmc.2026.075072

Received 24 October 2025; Accepted 18 December 2025; Issue published 12 March 2026

Abstract

Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack (LFA). Currently, there are limited topology obfuscation methods for protecting critical nodes, and the existing approaches mainly achieve obfuscation by extensively modifying network links, resulting in high costs. To address this issue, this paper proposes a low-cost network topology obfuscation method dedicated to critical node protection, with its core innovation lying in a lightweight obfuscation architecture based on Fake Node Clusters (FNCs). Firstly, the protected network is modeled as an undirected graph, and an adjacency matrix is constructed to quantify the network scale and structural characteristics. Then, a fake node cluster generation algorithm is designed to construct an FNC adapted to the target network. Finally, a heuristic obfuscated topology generation algorithm is proposed. By optimizing the deployment positions of Fake Nodes Clusters (FNCs) in the protected network, this algorithm effectively reduces the number of FNCs required to generate the obfuscated topology, further lowering the obfuscation cost. Extensive experiments were conducted on the public Topology Zoo dataset, categorizing network topologies by node count into small-scale ([0, 50)), medium-scale ([50, 100)), and large-scale ([100, 200)) groups. The experimental results demonstrate that the proposed approach achieves excellent obfuscation performance, reducing the critical node recognition rate to 0%. Compared to the typical method, EigenObfu, the proposed approach also reduces obfuscation costs by an average of 97.9%, 99.6%, and 99.3% for small, medium, and large-scale networks, respectively.

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