# Questions tagged [differential-privacy]

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### Intuitive explanation of the $\varepsilon$ parameter in differential privacy

I think I have a decent intuitive understanding of what the $\delta$ parameter means in $(\varepsilon,\delta)$-differential privacy: I can explain it to a non-specialist in terms of "what are the ...
1answer
418 views

### 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 $D,D'$ ...
1answer
380 views

### Parallel Composition of ($\epsilon, \delta$) differential privacy

I know that if there are $n$ functions $M_1, M_2, \cdots, M_n$ computed on disjoint subsets of the private database whose privacy guarantees are $\epsilon_1, \cdots ,\epsilon_n$ differential privacy, ...
1answer
219 views

### Differential privacy of “randomized responses”

We define randomized responses as follows: In a question that can be responded with a "Yes" or "No", a respondent is asked to flip a fair coin, in secret, and answer the truth if it comes up tails. ...
2answers
44 views

### What's the meaning of probabilities in differential privacy formula?

I don't understand what does it mean by "The probability is taken is over the coin tosses of K." Does it mean, the probability distribution is generated based on exactly same data but only the ...
1answer
247 views

### Difference between ε-differential privacy and (ε, δ)-differential privacy

I don't understand the necessity of introducing the additive term δ in the differential privacy definition. Moreover, reading different papers and blogs they say that because of the δ term the ...
1answer
172 views

### Differential privacy per record

Generally, differential privacy adds noise to a query result, such as a sum or an average, in an interactive way. Is there any way for implementing differential privacy such that noise will be added ...
1answer
146 views

### what does differential privacy (in machine learning) promise or guarantee?

I am recently reading some papers about privacy-preserving machine learning. Some works incorporate the idea of differential privacy to protect the privacy of the training dataset when the model is ...
1answer
93 views

### Differential privacy on multiple queries – what is the behavior?

Differential privacy framework still continue to be obscure in the following case: If I make a set of queries, I can join their output to restore the original data. For this issue we have composition ...
2answers
192 views

### Differential Privacy and appropriate noise distribution

In differential privacy solutions and more specifically for queries that they do entail counting the proposed solutions define the Laplace distribution that is best calibrated for low error. Other ...
1answer
76 views

### Laplace Mechanism Proof: Why this product operator?

The equation below shows the proof of Laplace mechanism for differential privacy. I am not understanding the product operator, is this a common rule?  \frac{p_x(z)}{p_y(z)} = \prod_{i=1}^{k}\left(\...
1answer
251 views

### What is ε in differential privacy?

In ε-differential privacy, what does the ε refer to? Is it privacy value or the notation used? Can anyone provide an example of differential privacy?
1answer
44 views

### Why does ε-differential privacy protect the subset of 1/ε edges in terms of graphs?

In the book The Algorithmic Foundations of Differential Privacy by Cynthia Dwork, Aaron Roth on page 24, databases that take the form of graphs are discussed. We could on the other hand consider ...
2answers
288 views

### Differential privacy definition

Differential privacy defines "privacy" of a mechanism $A$ as the "closeness" of the two distribution $Pr[A(D) \in S]$ and $Pr[A(D') \in S]$ where $D,D'$ differ in one element. And the distance between ...
2answers
56 views

### Sensitivity of probability measure in differential privacy

I know that we need some sort of sensitivity(global, local) to calculate noise that needs to be added for differential privacy. The noise is the maximum difference between two neighboring datasets. ...
2answers
223 views

### Why the definition in $\epsilon$-differential privacy is multiplicative rather than additive？

According to its mathematical definition, a random algorithm $M: D\rightarrow R$ satisfies $\epsilon$-differential privacy if the adjacent datasets $x, y \in D$ where $D$ is a whole dataset and ...
1answer
98 views

### what is the relationship between epsilon and sensitivity in the Differential-Privacy?

In some Differential-Privacy(DP) papers, they use epsilon as the x-axis in the figures of the experiments' result while other papers use the sensitivity. What is the relationship between epsilon and ...
0answers
41 views

### Differential privacy RAPPOR article proof doubts

Recently I've been trying to understand the RAPPOR proof: \begin{eqnarray*} P(B' = b' | B = b^*) & = & \left(\frac{1}{2}f\right)^{b'_1}\left(1 - \frac{1}{2}f\right)^{1 - b'_1} \times \ldots \\...
0answers
58 views

### Differential privacy and Shamir's scheme

I have been unable to find any proofs (for my own reference) that demonstrate that Shamir's secret sharing scheme does (or does not) satisfy the definition of $\textbf{differential privacy}$ as ...
0answers
114 views