English(EN) Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

新的RING攻击利用联邦学习中的差分隐私

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-15 17:53

研究人员开发了一种名为RING的新攻击方法，该方法利用联邦学习（FL）中的差分隐私（DP）来隐藏恶意更新。与先前的假设相反，DP可以掩盖后门攻击的统计特征，使现有防御措施失效。RING在针对最先进的防御措施时取得了90.3%的攻击成功率，凸显了DP-FL部署中存在的重大安全漏洞，并伴随着显著的效用权衡。 AI

影响暴露了差分隐私联邦学习中的一个基本安全漏洞，可能需要新的防御机制。

排序理由该集群包含一篇在arXiv上发表的研究论文，详细介绍了一种针对差分隐私联邦学习的新型攻击方法。

在 arXiv cs.LG 阅读 →

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报道来源 [2]

arXiv cs.LG TIER_1 English(EN) · Xiaolin Li, Ning Wang, Ninghui Li, Wenhai Sun · 2026-06-16 04:00

Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

arXiv:2606.17035v1 Announce Type: new Abstract: Prior research suggests that differential privacy (DP) inherently enhances the robustness of federated learning (FL) against backdoor attacks. In this paper, we challenge this assumption. Through an empirical analysis of two baselin…
arXiv cs.LG TIER_1 English(EN) · Wenhai Sun · 2026-06-15 17:53

Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

Prior research suggests that differential privacy (DP) inherently enhances the robustness of federated learning (FL) against backdoor attacks. In this paper, we challenge this assumption. Through an empirical analysis of two baseline attack strategies, we uncover a fundamental te…

报道来源 [2]

Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

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