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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 11

Domain mapping enhancement and adversarial gain aggregation algorithm for IoT security

Gu Yue1,2
Liu Miao1,2
Sun Zhenxing3
1. School of Electronics & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
2. School of Electronics and Information Engineer, Wuxi University, Wuxi Jiangsu 210045, China
3. Qinhuangdao Branch of Northeast Petroleum University, Qinhuangdao Hebei 066044, China
DOI: 10.19734/j.issn.1001-3695.2025.05.0119

Abstract

To ensure data security and expand the application of federated learning in heterogeneous Internet of Things (IoT) environments, this paper proposed a federated learning framework that integrates domain mapping enhancement and adversarial gain aggregation mechanisms. The framework used domain mapping enhancement to improve feature extraction capability and increase feature separability, thereby improving model performance. It also applied an adversarial gain aggregation method to dynamically adjust client weights during aggregation, reducing performance degradation of the global model caused by heterogeneity. Compared with FedGen, the framework achieved a 6.64 percentage point improvement in accuracy. The experimental results show that the proposed framework effectively mitigates the impact of heterogeneity, performs well across four experimental scenarios, and significantly improves the convergence stability and overall accuracy of models in IoT applications.

Foundation Support

国家自然科学基金资助项目(61601111)
黑龙江省自然科学基金资助项目(LH2022F004)
"锡山英才计划"领军人才项目(2024xsyc002)
无锡学院人才启动项目(2024r014)
无锡学院引进人才科研启动专项经费(2024r014)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.05.0119
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 11

Publish History

[2025-07-24] Accepted Paper

Cite This Article

谷越, 刘苗, 孙振兴. 面向物联网安全的域映射增强与对抗增益聚合算法 [J]. 计算机应用研究, 2025, 42 (11). (2025-07-24). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0119. (Gu Yue, Liu Miao, Sun Zhenxing. Domain mapping enhancement and adversarial gain aggregation algorithm for IoT security [J]. Application Research of Computers, 2025, 42 (11). (2025-07-24). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0119. )

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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