16 citations · 20 across the 4 of their papers we have counts for
4 papers
A Shuffling Framework for Local Differential Privacy
Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri +1
ldp deployments are vulnerable to inference attacks as an adversary can link the noisy responses to their identity and subsequently, auxiliary information using the order of the da…
Location Trace Privacy Under Conditional Priors
Casey Meehan, Kamalika Chaudhuri
Providing meaningful privacy to users of location based services is particularly challenging when multiple locations are revealed in a short period of time. This is primarily due t…
A Non-Parametric Test to Detect Data-Copying in Generative Models
Casey Meehan, Kamalika Chaudhuri, Sanjoy Dasgupta
Detecting overfitting in generative models is an important challenge in machine learning. In this work, we formalize a form of overfitting that we call {\em{data-copying}} -- where…
Location Trace Privacy Under Conditional Priors
Casey Meehan, Kamalika Chaudhuri
Providing meaningful privacy to users of location based services is particularly challenging when multiple locations are revealed in a short period of time. This is primarily due t…