1 citations · 1 across the 5 of their papers we have counts for
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Information-Theoretic Privacy with General Distortion Constraints
Kousha Kalantari, Oliver Kosut, Lalitha Sankar
The privacy-utility tradeoff problem is formulated as determining the privacy mechanism (random mapping) that minimizes the mutual information (a metric for privacy leakage) betwee…
Reveal-or-Obscure: A Differentially Private Sampling Algorithm for Discrete Distributions
Naima Tasnim, Atefeh Gilani, Lalitha Sankar +1
We introduce a differentially private (DP) algorithm called reveal-or-obscure (ROO) to generate a single representative sample from a dataset of observations drawn i.i.d. from…
An information theorist's tour of differential privacy
Anand D. Sarwate, Flavio P. Calmon, Oliver Kosut +1
Since being proposed in 2006, differential privacy has become a standard method for quantifying certain risks in publishing or sharing analyses of sensitive data. At its heart, dif…
Optimizing Noise Distributions for Differential Privacy
Atefeh Gilani, Juan Felipe Gomez, Shahab Asoodeh +3
We propose a unified optimization framework for designing continuous and discrete noise distributions that ensure differential privacy (DP) by minimizing Rényi DP, a variant of DP…