Sybil attacks detection for dynamic environment in federated learning

Lihuang Lin; Xi Zhu; Junbo Wang

doi:10.1117/12.3026024

6 May 2024 Sybil attacks detection for dynamic environment in federated learning

Lihuang Lin, Xi Zhu, Junbo Wang

Proceedings Volume 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023); 131610G (2024) https://doi.org/10.1117/12.3026024
Event: Fourth International Conference on Telecommunications, Optics and Computer Science (TOCS 2023), 2023, Xi’an, China

Abstract

Federated learning can utilize its distributed structure to protect data privacy security of clients and improve efficiency of machine learning. However, its distributed framework also make itself be susceptible to sybil attacks. While previous research has already proposed defense methods to address this issue, they often fail to guarantee effective performance in a dynamic federated learning system, where some clients dynamically join in and out. To tackle this problem, our paper introduces a novel defense method specifically designed to mitigate sybil attacks in dynamic federated learning scenario. Our proposed method consists of three mechanisms: similarity mechanism, validation mechanism, and reputation mechanism. These mechanisms can address the problem of missing information and effectively resist sybil attacks in dynamic federated learning. We evaluate the performance of our method on the MNIST and KDDCup datasets and demonstrate its advanced ability in defending against sybil attacks in dynamic federated learning compared to existing methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lihuang Lin, Xi Zhu, and Junbo Wang "Sybil attacks detection for dynamic environment in federated learning", Proc. SPIE 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023), 131610G (6 May 2024); https://doi.org/10.1117/12.3026024

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KEYWORDS

Machine learning

Data modeling

Education and training

Defense and security

Process modeling

Design

Distance measurement

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