Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [differential-privacy]

40 questions
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Has the journal Science endorsed the Garden of Forking Pathes Analyses?

The idea of adaptive data analysis is that you alter your plan for analyzing the data as you learn more about it. In the case of exploratory data analysis (EDA), this is generally a good idea (you are often looking for unforeseen patterns in the…
Cliff AB
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What is meant by "Laplace noise"?

I am currently writing algorithm for differential privacy using the Laplace mechanism. Unfortunately I have no background in statistics, therefore a lot of terms are unknown to me. So now I'm stumbling over the term: Laplace noise. To make a…
Axolotl
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How to generate a sanitized dataset using Differential privacy?

I'm learning about differential privacy. I understand the concept behind differential privacy, that you can add a small noise to the query to mask the true value using transformations like Laplace or exponential. I'm not able to grasp how can I use…
pauli
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What are global sensitivity and local sensitivity in differential privacy?

I am learning differential privacy now, and there is no one surrounding I can ask questions about differential privacy. I am confused about the definitions of the global sensitivity and local sensitivity. The two definitions are from the book…
Meow
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Most powerful test bounds in differential privacy setting

I am interested in the setting of differential privacy- let's say a random function $\mathcal{D}:X\to\mathbb{R}$ discriminates between (distinct) $x, y \in X$ in a differentially private way if $$ \mathbb{P}(\mathcal{D}(x) \in S) \le e^\epsilon…
P.Windridge
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Privacy through moving averages?

I am considering the following hypothetical situation: I have a time series of data. In general, 'the public' should have access to features of this data. However, making the time series available would constitute a privacy leak. I am considering…
Elle Najt
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What is the purpose of using a Laplacian distribution in adding noise for Differential Privacy?

I am reading up on Differential Privacy and it is mentioned that the technique relies on adding some controlled noise to the release of responses to queries towards a statistical database. This is done so as to preserve the privacy of the owners…
Pieru Poika
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Adding Laplace noise to a learned neural network

My question is related to the concept of differential privacy and deep learning. I found many papers to learn neural networks with differential privacy, but is it also possible to achieve differential privacy if you already have a non-private model…
Max Moser
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Communicating aggregate percentage changes in data without exposing individual contributors

So i have a dataset that tracks widget production from 100 different factories, each individually owned and highly competitive. Each line contains the factory name, the date of production, and the # of widgets produced. As expected, some widget…
Jay
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Differential privacy of identity query

I am trying to understand some of the papers that present identity query mechanisms that satisfies differential privacy, for example the compressive mechanism which uses what they call a universal mechanism. What I mean by identity query is: given a…
Jon doe
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Effect of exp(ϵ) in Differential Privacy Definition

I am reading about differential privacy and would like to understand the implications of the different values of $\varepsilon$ in the definition below: $$\mathbb{P}[K(D_1) \in \mathcal{S}] \leqslant \exp(\varepsilon) \times \mathbb{P}[K(D_2) \in…
DSPNewbie
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Differential Privacy: why $\delta$ negligible on the row numbers?

The definition of differential privacy says that an algorithm $M$ is $(\epsilon,\delta)$-differentially private if $$P(M(x \in D) \in S)\leq e^\epsilon P(M(x \in D')\in S) + \delta$$ where $D,D'$ differ by one row and $\delta$ is …
volperossa
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How should one calculate the confidence interval in 2020 census data, which uses differential privacy?

In 2020, the U.S. Census Bureau began injecting noise into census counts using a differential privacy technique. See here for a popular press description and here for some official literature. The introduction of this noise makes counts from…
John J.
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Upper Bound and Lower Bound on Means when Distributions are bounded?

Suppose we have two different probability distributions $p, q$ defined on input $x \in [0,1]$. We know that for any value of $x$ in the domain, we have $\exp^{-a} \leq \frac{p(x)}{q(x)} \leq \exp^{a} $, here $a$ is a fixed number. In other words,…
Kieu Anh Dang
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What is statistical difference?

In the paper "Calibrating Noise to Sensitivity in Private Data Analysis" by Dwork et al., the term "statistical difference" is used as following (in page 280): Finally, if a $1 − \gamma$ fraction of the $z$’s are $\delta$-good for a particular pair…
oicrisah
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