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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 3

Global community hiding algorithm based on self-attention mechanism

Feng Zhichaoa
Zhang Bohana
Jing Junchanga
Li Yongboa
Liu Donga,b,c
a. College of Computer and Information Engineering, b. Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province, c. Big Data Engineering Lab of Teaching Resources & assessment of Education Quality, Henan Normal University, Xinxiang 453007, China
DOI: 10.19734/j.issn.1001-3695.2025.06.0267

Abstract

Community detection algorithms demonstrate strong capability in mining network data but simultaneously pose risks of user information leakage. To address this issue, researchers actively explore community hiding as a solution. However, most existing studies on community hiding focus on topological networks and achieve limited progress in attributed networks. To overcome this limitation, this study proposes a Self-Attention mechanism Network Community Hiding (SANCH) algorithm. The algorithm models the global dependencies among node attributes using a self-attention mechanism and generates adversarial perturbations by integrating structural information of the graph. It computes attention weights between nodes to derive node embeddings and then estimates the probability of link existence. Based on a predefined perturbation budget, the algorithm selects links with the greatest impact on the community structure for addition or deletion, thereby achieving effective community hiding. Experimental results demonstrate that SANCH delivers outstanding hiding performance and robustness against various community detection algorithms.

Foundation Support

国家自然科学基金资助项目(62072160)
河南省科技攻关计划资助项目(242102211076)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.06.0267
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 3

Publish History

[2025-11-18] Accepted Paper

Cite This Article

冯志超, 张博瀚, 荆军昌, 等. 基于自注意力机制的全局社区隐藏算法 [J]. 计算机应用研究, 2026, 43 (3). (2025-11-18). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0267. (Feng Zhichao, Zhang Bohan, Jing Junchang, et al. Global community hiding algorithm based on self-attention mechanism [J]. Application Research of Computers, 2026, 43 (3). (2025-11-18). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0267. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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