论文笔记：Local Differential Privacy: a tutorial - 知乎
本地差分隐私（ldp）是一种最先进的方法，在保护每个用户隐私的同时允许统计计算。 与差分隐私（DP）不同，由于在本地向用户输入添加了噪声，因此不需要一个可信的数据中心。
local differential privacy summary - 知乎 - 知乎专栏
根据pure LDP的定义， p^* 指的是，当某一个输入被扰动后的结果“支持”时，把这一输入还映射到这个结果“支持”的item上去。 也就是说，这里我们的 p^* 是指，当 H(v) = b 时，我们对 b 扰 …
4. Local Differential Privacy - 知乎 - 知乎专栏
为应对Untrusted Curator model，可以采用：Local Differential Privacy (LDP)，Intermediate Trust Models，Federated Learning等，这里仅介绍LDP。 LDP：终端自行利用Differential Privacy机 …
局部差分隐私（Local Differential Privacy）的概念如何理解？ - 知乎
拿Uber的SQL DP论文 (参考1)来举例，可以很好的解释这个差别，SQL DP同时引入一个新的敏感度方法：弹性敏感度 (Elastic Sensitivity)来解决局部差分隐私可能导致噪音无界的问题。 可以 …
Local differential privacy - Wikipedia
Local differential privacy (LDP) is a model of differential privacy with the added requirement that if an adversary has access to the personal responses of an individual in the database, that …
LDP-Purifier: Defending against Poisoning Attacks in Local
Oct 27, 2024 · We propose the defense protocol LDP-Purifier to rectify the poisoned histogram and suppress the utility damage by poisoning. As a post-processing method, it can be applied …
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