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作者: _Mia_

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【论文阅读笔记】Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training

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原创 2025-03-17 16:48:13 · 974 阅读 · 0 评论
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training

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原创 2025-02-26 10:55:24 · 889 阅读 · 0 评论
【论文阅读笔记】A Stability-Enhanced Dynamic Backdoor Defense in Federated Learning for IIoT

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原创 2024-08-16 17:22:19 · 1083 阅读 · 0 评论
【论文阅读笔记】SDBA: A Stealthy and Long-Lasting Durable Backdoor Attack in Federated Learning

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原创 2024-10-10 10:44:35 · 969 阅读 · 0 评论
【论文阅读笔记】Eavesdrop the Composition Proportion of Training Labels in Federated Learning

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原创 2024-10-10 10:35:57 · 1026 阅读 · 0 评论
【论文阅读笔记】CrowdGuard: Federated Backdoor Detection in Federated Learning

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原创 2024-05-13 15:01:47 · 1482 阅读 · 2 评论
【论文阅读笔记】Detecting AI Trojans Using Meta Neural Analysis

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原创 2023-11-10 19:59:46 · 1635 阅读 · 7 评论
【论文阅读笔】TEAR: Exploring Temporal Evolution of Adversarial Robustness for Membership Inference Attacks

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原创 2023-10-12 10:45:27 · 287 阅读 · 0 评论
【论文阅读笔记】Shielding collaborative learning:Mitigating poisoning attacks through client-side detection.

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原创 2023-09-06 15:19:39 · 368 阅读 · 1 评论
【论文阅读笔记】Attack-Resistant Federated Learning with Residual-based Reweighting

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原创 2023-07-12 11:10:59 · 1051 阅读 · 1 评论
【论文阅读】Secure Partial Aggregation: Making Federated Learning More Robust for Industry 4.0 Application

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原创 2023-07-11 10:33:12 · 276 阅读 · 0 评论
【论文阅读笔记】Analyzing Federated Learning through an Adversarial Lens

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原创 2023-07-03 14:17:45 · 1098 阅读 · 0 评论
【论文阅读笔记】Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

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原创 2023-06-14 10:38:40 · 3245 阅读 · 1 评论
【论文阅读笔记】CRFL: Certifiably Robust Federated Learning against Backdoor Attacks

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原创 2023-05-29 21:15:55 · 1075 阅读 · 0 评论
【论文阅读笔记】BaFFLe: Backdoor Detection via Feedback-based Federated Learning

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原创 2023-05-23 12:33:13 · 913 阅读 · 1 评论
【论文阅读】Resisting Distributed Backdoor Attacks in Federated Learning: A Dynamic Norm Clipping Approach

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原创 2023-05-19 16:02:16 · 368 阅读 · 1 评论
【论文阅读笔记】Federated Unlearning with Knowledge Distillation

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原创 2023-05-19 10:28:14 · 823 阅读 · 2 评论
【论文阅读笔记】FedEraser: Enabling Efficient Client-Level Data Removal from Federated Learning Models

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原创 2023-05-18 08:49:13 · 1049 阅读 · 1 评论
【论文阅读笔记】Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

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原创 2023-05-12 14:34:24 · 205 阅读 · 1 评论
【论文阅读笔记】Dynamic backdoor attacks against federated learning

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原创 2023-05-11 17:33:16 · 576 阅读 · 0 评论
【论文阅读笔记】ARIBA: Towards Accurate and Robust Identification of Backdoor Attacks in Federated Learning

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原创 2023-05-10 16:30:50 · 204 阅读 · 0 评论
【论文阅读笔记】Neurotoxin: Durable Backdoors in Federated Learning

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原创 2023-05-04 17:28:59 · 694 阅读 · 1 评论
【论文阅读笔记】Robust Federated Learning with Attack-Adaptive Aggregation

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原创 2023-04-27 17:50:02 · 366 阅读 · 1 评论
【论文阅读笔记】Learning to Detect Malicious Clients for Robust Federated Learning

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原创 2023-04-27 15:21:09 · 421 阅读 · 1 评论
【论文阅读笔记】The Limitations of Federated Learning in Sybil Settings

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原创 2023-04-25 16:37:12 · 1382 阅读 · 1 评论
【论文阅读笔记】Coordinated Backdoor Attacks against Federated Learning with Model-Dependent Triggers

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原创 2023-04-18 18:10:48 · 367 阅读 · 1 评论
【论文阅读笔记】Data Poisoning Attacks Against Federated Learning Systems

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原创 2023-04-18 18:57:02 · 1391 阅读 · 5 评论
【论文阅读笔记】Attack of the Tails: Yes, You Really Can Backdoor Federated

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原创 2023-04-17 14:50:59 · 988 阅读 · 1 评论
【论文阅读笔记】PPA: Preference Profiling Attack Against Federated Learning

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原创 2023-03-15 16:49:43 · 1121 阅读 · 7 评论
【论文阅读笔记】FLAME: Taming Backdoors in Federated Learning

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原创 2023-03-02 17:51:47 · 1736 阅读 · 0 评论
【论文阅读笔记】Efficient and Secure Federated Learning With Verifiable Weighted Average Aggregation

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原创 2023-02-28 17:22:32 · 541 阅读 · 4 评论
【论文阅读笔记】DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection

论文阅读笔记DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection，区分中毒客户端模型与良性客户端模型

原创 2023-02-21 16:58:46 · 1040 阅读 · 2 评论

论文笔记

作者: _Mia_

【论文阅读笔记】Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training

Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training

【论文阅读笔记】A Stability-Enhanced Dynamic Backdoor Defense in Federated Learning for IIoT

【论文阅读笔记】SDBA: A Stealthy and Long-Lasting Durable Backdoor Attack in Federated Learning

【论文阅读笔记】Eavesdrop the Composition Proportion of Training Labels in Federated Learning

【论文阅读笔记】CrowdGuard: Federated Backdoor Detection in Federated Learning

【论文阅读笔记】Detecting AI Trojans Using Meta Neural Analysis

【论文阅读笔】TEAR: Exploring Temporal Evolution of Adversarial Robustness for Membership Inference Attacks

【论文阅读笔记】Shielding collaborative learning:Mitigating poisoning attacks through client-side detection.

【论文阅读笔记】Attack-Resistant Federated Learning with Residual-based Reweighting

【论文阅读】Secure Partial Aggregation: Making Federated Learning More Robust for Industry 4.0 Application

【论文阅读笔记】Analyzing Federated Learning through an Adversarial Lens

【论文阅读笔记】Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

【论文阅读笔记】CRFL: Certifiably Robust Federated Learning against Backdoor Attacks

【论文阅读笔记】BaFFLe: Backdoor Detection via Feedback-based Federated Learning

【论文阅读】Resisting Distributed Backdoor Attacks in Federated Learning: A Dynamic Norm Clipping Approach

【论文阅读笔记】Federated Unlearning with Knowledge Distillation

【论文阅读笔记】FedEraser: Enabling Efficient Client-Level Data Removal from Federated Learning Models

【论文阅读笔记】Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

【论文阅读笔记】Dynamic backdoor attacks against federated learning

【论文阅读笔记】ARIBA: Towards Accurate and Robust Identification of Backdoor Attacks in Federated Learning

【论文阅读笔记】Neurotoxin: Durable Backdoors in Federated Learning

【论文阅读笔记】Robust Federated Learning with Attack-Adaptive Aggregation

【论文阅读笔记】Learning to Detect Malicious Clients for Robust Federated Learning

【论文阅读笔记】The Limitations of Federated Learning in Sybil Settings

【论文阅读笔记】Coordinated Backdoor Attacks against Federated Learning with Model-Dependent Triggers

【论文阅读笔记】Data Poisoning Attacks Against Federated Learning Systems

【论文阅读笔记】Attack of the Tails: Yes, You Really Can Backdoor Federated

【论文阅读笔记】PPA: Preference Profiling Attack Against Federated Learning

【论文阅读笔记】FLAME: Taming Backdoors in Federated Learning

【论文阅读笔记】Efficient and Secure Federated Learning With Verifiable Weighted Average Aggregation

【论文阅读笔记】DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection