利用后门神经元约束和模型伪装，通过频域对联合学习进行隐形后门攻击

IF 3.7 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2024-08-27 DOI:10.1109/jetcas.2024.3450527

Yanqi Qiao, Dazhuang Liu, Rui Wang, Kaitai Liang

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Stealthy Backdoor Attack against Federated Learning through Frequency Domain by Backdoor Neuron Constraint and Model Camouflage

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来源期刊

IEEE Journal on Emerging and Selected Topics in Circuits and Systems ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

8.50

自引率

2.20%

发文量

期刊介绍： The IEEE Journal on Emerging and Selected Topics in Circuits and Systems is published quarterly and solicits, with particular emphasis on emerging areas, special issues on topics that cover the entire scope of the IEEE Circuits and Systems (CAS) Society, namely the theory, analysis, design, tools, and implementation of circuits and systems, spanning their theoretical foundations, applications, and architectures for signal and information processing.