# Questions tagged [data-privacy]

Data privacy refers to (cryptographic) methods to prevent the disclosure of sensitive (identifying) information of persons.

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### Adding the same noise to all element of a vector is Differential privacy

In Differential privacy, if we add a $N$-dimension private vector with $N$-dimension Laplace or Gauss noise, we obtain differential privacy. However, if we only generate a 1-dimension noise to add it ...
172 views

### Zero knowledge proof in smart parking managment systems

I read this paper on protecting user privacy in smart parking management system. It talks about using zero knowledge proofs to protect privacy but I am not certain how they do it. My assumption is ...
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### 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. ...
736 views

### 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 ...
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### Data Security and Encryption

I have a research paper on data security using proxy re-encryption, and I need to provide an answer to a reviewer's comment. However, I have no idea on what to do or how to answer it. The security ...
110 views

### Oblivious transfer where neither party learns the index of the message

In a traditional oblivious transfer setting, the sender has a list $(x_1, x_2, ... , x_n) \in G$ where $G$ is the chosen group. The receiver has $b \in \mathbb{N}$, such that engaging in the protocol ...
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### Directional vector privacy-preserving techniques

I'm new to cryptography, and I wonder if it's possible to temporarily track users by observing directional vectors in Mobile-Ad-Hoc-Networks, and if there are any methods, in case it is trackable, to ...
137 views

### how many iterations of SHA3 (keccak256) hashing would be required to provide reasonable protection for the following data structure?

((A , B , C) , (D , E , F, G, H)) Where: A is 0x0-0xF, (1 of 16) B is 0x00-0xFF (1 of 256) C is an 8 digit integer D is a one of a list of one hundred words padded to 12 characters E is a one ...
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### What is $z_b$ in this introduction to Private Information Retrieval?

I was trying to read this introduction to private information retrieval. On page 12 of the document, a scheme for 1-DB private information retrieval is discussed. I was unable to understand one of the ...
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### How to adapt the equation of Gaussian mechanism noise based on number of executions

I'm trying to build a differentially private machine learning model. I'm using the Gaussian mechanism to calculate the required noise amount based on pre-defined privacy budget value 𝜖 The equation ...
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### Mechanisms for masking identifying unique IDs with non-identifying unique IDs to protect privacy?

I need to suggest mechanisms for masking unique codes in a database with different unique codes that are not derived from the original unique codes, but are equivalently unique in that they could ...
63 views

### Content Key Encryption for Multi-User data access

I recently worked out a concept for a use-case, but I'm not sure if my approach is good enough. So I would appreciate feedback and things to look out for, as I'm fairly new to this field. A User can ...
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### Is using Fiat-shamir Heuristic safe?

What I'd like to do is to have the Prover store a value x where x remains hidden. From x, I'...
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### Calculating the privacy that Renyi ($\epsilon, \delta$) Differential Privacy satisfies

I add differential privacy (DP) to my machine learning models by using PyTorch-DP. PyTorch-DP supplies me with the values: $\epsilon$ and $\delta$. I know that the $\epsilon$ tells us something about ...
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### Differential Privacy: What is the 'game' between data holder and adversary?

I have been reading the Differential Privacy (DP) literature for some time to get familiar with it. I feel comfortable with the Math and Stats foundations of it, but I am suffering a bit from the '...
82 views