Results 11 to 20 of about 64,907 (298)

Random Differential Privacy

open access: yesThe Journal of Privacy and Confidentiality, 2013
We propose a relaxed privacy definition called {\em random differential privacy} (RDP). Differential privacy requires that adding any new observation to a database will have small effect on the output of the data-release procedure.
Robert Hall   +2 more
doaj   +5 more sources

Heterogeneous Differential Privacy

open access: yesThe Journal of Privacy and Confidentiality, 2017
The massive collection of personal data by personalization systems has rendered the preservation of privacy of individuals more and more difficult. Most of the proposed approaches to preserve privacy in personalization systems usually address this issue ...
Mohammad Alaggan   +2 more
doaj   +5 more sources

Equitable differential privacy [PDF]

open access: yesFrontiers in Big Data
Differential privacy (DP) has been in the public spotlight since the announcement of its use in the 2020 U.S. Census. While DP algorithms have substantially improved the confidentiality protections provided to Census respondents, concerns have been ...
Vasundhara Kaul, Tamalika Mukherjee
doaj   +4 more sources

Gaussian Differential Privacy [PDF]

open access: yesJournal of the Royal Statistical Society Series B: Statistical Methodology, 2022
AbstractIn the past decade, differential privacy has seen remarkable success as a rigorous and practical formalization of data privacy. This privacy definition and its divergence based relaxations, however, have several acknowledged weaknesses, either in handling composition of private algorithms or in analysing important primitives like privacy ...
Aaron Roth, Weijie J Su
exaly   +3 more sources

On the 'Semantics' of Differential Privacy: A Bayesian Formulation

open access: yesThe Journal of Privacy and Confidentiality, 2014
Differential privacy is a definition of privacy for algorithms that analyze and publish information about statistical databases. It is often claimed that differential privacy provides guarantees against adversaries with arbitrary side information.
Shiva P. Kasiviswanathan, Adam Smith
doaj   +2 more sources

Individual Differential Privacy: A Utility-Preserving Formulation of Differential Privacy Guarantees [PDF]

open access: yesIEEE Transactions on Information Forensics and Security, 2017
Differential privacy is a popular privacy model within the research community because of the strong privacy guarantee it offers, namely that the presence or absence of any individual in a data set does not significantly influence the results of analyses on the data set.
Jordi Soria-Comas   +2 more
exaly   +6 more sources

Privacy-Preserving Monotonicity of Differential Privacy Mechanisms

open access: yesApplied Sciences, 2018
Differential privacy mechanisms can offer a trade-off between privacy and utility by using privacy metrics and utility metrics. The trade-off of differential privacy shows that one thing increases and another decreases in terms of privacy metrics and ...
Hai Liu   +5 more
doaj   +2 more sources

Generalized Rainbow Differential Privacy

open access: yesThe Journal of Privacy and Confidentiality
We study a new framework for designing differentially private (DP) mechanisms via randomized graph colorings, called rainbow differential privacy. In this framework, datasets are nodes in a graph, and two neighboring datasets are connected by an edge ...
Yuzhou Gu   +6 more
doaj   +2 more sources

Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy

open access: yesThe Journal of Privacy and Confidentiality, 2021
We give a simple, computationally efficient, and node-differentially-private algorithm for estimating the parameter of an Erdos-Renyi graph---that is, estimating p in a G(n,p)---with near-optimal accuracy.
Adam Sealfon, Jonathan Ullman
doaj   +3 more sources

SoK: Differential privacies [PDF]

open access: yesProceedings on Privacy Enhancing Technologies, 2020
AbstractShortly after it was first introduced in 2006,differential privacybecame the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions.
Damien Desfontaines, Balázs Pejó
openaire   +3 more sources

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