中国物理B ›› 2023, Vol. 32 ›› Issue (6): 68902-068902.doi: 10.1088/1674-1056/acb9fc

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Robust multi-task distributed estimation based on generalized maximum correntropy criterion

Qian Hu(胡倩), Feng Chen(陈枫), and Ming Ye(叶明)   

  1. College of Artificial Intelligence, Southwest University, Chongqing 400715, China
  • 收稿日期:2022-08-12 修回日期:2023-01-09 接受日期:2023-02-08 出版日期:2023-05-17 发布日期:2023-05-24
  • 通讯作者: Ming Ye E-mail:zmxym@swu.edu.cn

Robust multi-task distributed estimation based on generalized maximum correntropy criterion

Qian Hu(胡倩), Feng Chen(陈枫), and Ming Ye(叶明)   

  1. College of Artificial Intelligence, Southwest University, Chongqing 400715, China
  • Received:2022-08-12 Revised:2023-01-09 Accepted:2023-02-08 Online:2023-05-17 Published:2023-05-24
  • Contact: Ming Ye E-mail:zmxym@swu.edu.cn

摘要: False data injection (FDI) attacks are common in the distributed estimation of multi-task network environments, so an attack detection strategy is designed by combining the generalized maximum correntropy criterion. Based on this, we propose a diffusion least-mean-square algorithm based on the generalized maximum correntropy criterion (GMCC-DLMS) for multi-task networks. The algorithm achieves gratifying estimation results. Even more, compared to the related work, it has better robustness when the number of attacked nodes increases. Moreover, the assumption about the number of attacked nodes is relaxed, which is applicable to multi-task environments. In addition, the performance of the proposed GMCC-DLMS algorithm is analyzed in the mean and mean-square senses. Finally, simulation experiments confirm the performance and effectiveness against FDI attacks of the algorithm.

关键词: distributed estimation, generalized correntropy, multi-task networks, adaptive filtering

Abstract: False data injection (FDI) attacks are common in the distributed estimation of multi-task network environments, so an attack detection strategy is designed by combining the generalized maximum correntropy criterion. Based on this, we propose a diffusion least-mean-square algorithm based on the generalized maximum correntropy criterion (GMCC-DLMS) for multi-task networks. The algorithm achieves gratifying estimation results. Even more, compared to the related work, it has better robustness when the number of attacked nodes increases. Moreover, the assumption about the number of attacked nodes is relaxed, which is applicable to multi-task environments. In addition, the performance of the proposed GMCC-DLMS algorithm is analyzed in the mean and mean-square senses. Finally, simulation experiments confirm the performance and effectiveness against FDI attacks of the algorithm.

Key words: distributed estimation, generalized correntropy, multi-task networks, adaptive filtering

中图分类号:  (Entropy and other measures of information)

  • 89.70.Cf
84.40.Ua (Telecommunications: signal transmission and processing; communication satellites) 89.70.-a (Information and communication theory) 43.60.Jn (Source localization and parameter estimation)