DAGUARD: distributed backdoor attack defense scheme under federated learning

Shengxing YU; Zekai CHEN; Zhong CHEN; Ximeng LIU

doi:10.11959/j.issn.1000-436x.2023086

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DAGUARD: distributed backdoor attack defense scheme under federated learning

Papers | 更新时间：2024-06-06

- DAGUARD: distributed backdoor attack defense scheme under federated learning
- Journal on Communications Vol. 44, Issue 5, Pages: 110-122(2023)
- 作者机构：
  
  1. 北京大学计算机学院，北京 100871
  2. 福州大学计算机与大数据学院/软件学院，福建福州 350108
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62072109);The National Natural Science Foundation of China(62102422)
- DOI：10.11959/j.issn.1000-436x.2023086
  CLC： TN92
- Online First：2023-05，
  
  Published：25 May 2023
- 稿件说明：
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Shengxing YU, Zekai CHEN, Zhong CHEN, et al. DAGUARD: distributed backdoor attack defense scheme under federated learning[J]. Journal on Communications, 2023, 44(5): 110-122.
DOI：

Shengxing YU, Zekai CHEN, Zhong CHEN, et al. DAGUARD: distributed backdoor attack defense scheme under federated learning[J]. Journal on Communications, 2023, 44(5): 110-122. DOI： 10.11959/j.issn.1000-436x.2023086.

摘要

为了解决联邦学习下的分布式后门攻击等问题，基于服务器挑选最多不超过半数恶意客户端进行全局聚合的假设，提出了一种联邦学习下的分布式后门防御方案（DAGUARD）。设计了三元组梯度优化算法局部更新策略（TernGrad）以解决梯度局部调整的后门攻击和推理攻击、自适应密度聚类防御方案（AdaptDBSCAN）以解决角度偏较大的后门攻击、自适应裁剪方案以限制放大梯度的后门增强攻击和自适应加噪方案以削弱分布式后门攻击。实验结果表明，在联邦学习场景下，所提方案相比现有的防御策略具有更好的防御性能和防御稳定性。

Abstract

In order to solve the problems of distributed backdoor attack under federated learning

a distributed backdoor attack defense scheme (DAGUARD) under federated learning was proposed based on the assumption that the server selected no more than half of malicious clients for global aggregation.The partial update strategy of the triple gradient optimization algorithm (TernGrad) was designed to solve the backdoor attack and inference attack

an adaptive density clustering defense scheme was designed to solve the backdoor attacks with relatively large angle deflection

the adaptive clipping scheme was designed to limit the enhancement backdoor attack that amplify the gradients and the adaptive noise-enhancing scheme was designed to weaken distributed backdoor attacks.The experimental results show that in the federated learning scenario

the proposed scheme has better defense performance and defense stability than existing defense strategies.

关键词

Keywords

references

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