这两个概念都具有the finest resolution,因为它们可以保护一个客户数据的单个记录。我们依赖的隐私定义是潜在隐私f-differential privacy,是其高斯潜在隐私 (GDP) 的子家族 (Dong等人,2019)。 2.我们提出了一个通用的联合学习框架PriFedSync,其中包含最先进的联合学习算法。框架不假定可信的中央聚合器。它可以容纳个...
关于「联邦学习」的名字还有一个故事：在早期国内将「FederatedLearning」大多翻译为「联合学习」，现多称...
如果顺利，其他联邦机构可能也会使用这种方法。加拿大和英国等国也在关注该技术。
Differential Privacy (DP), as an advanced privacy protection technology, introduces random noise during data queries or model updates, further enhancing the privacy protection capability of Federated Learning. This paper delves into the theory, technology, development, and futur...
Federated Learning with Differential Privacy:Algorithms and Performance Analysis 2024/2/11 大四做毕设的时候第一次读这篇论文,当时只读了前一部分,后面关于收敛界推导证明的部分没有看,现在重新完整阅读一下这篇文章。 本文贡献 提出了一种基于差分隐私 (DP) 概念的新框架,其中在聚合之前将人工噪声添加到客户端的...
In this experiment, we use Differential Private Federated Learning (DP-FL) to ensure data privacy. Differential Privacy (DP) was not considered in experiment series 1 since the objective was to study the effects of data size, distribution, and the number of clients on the performance of distrib...
This article proposes a privacy-preserving approach for learning effective personalized models on distributed user data while guaranteeing the differential privacy of user data. Practical issues in a distributed learning system such as user heterogeneity are considered in the proposed approach. In addition...
In this report, we showcase our empirical benchmark of the effect of the number of clients and the addition of differential privacy (DP) mechanisms on the performance of the model on different types of data. Our results show that non-i.i.d and small datasets have the highest decrease in...
D. ??? 差分隐私(Differential privacy) E. ??? 安全多方计算(Secure multiparty computation(SMC)) F. ??? 同态加密(Homomorphic encryption) G.??? 鲁棒性聚合(Robust aggregation) ??? 舞、Related Work ??? 柳、Conclusion ??? 悟:我的获悉 本文的主要贡献...
差分隐私(Differential Privacy)。另一个工作领域使用差分隐私[18]或k-匿名[63]技术来保护数据隐私[1,12,42,61]。差分隐私、k-匿名(k-anonymity)和多样化的方法[3]包括给数据添加噪声,或使用泛化方法模糊某些敏感属性,直到第三方无法区分个人,从而使数据无法恢复以保护用户隐私。然而,这些方法的根本原因仍然是需要将...