3 citations · 8 across the 15 of their papers we have counts for
19 papers
-Diversity: Linkage-Robustness via a Composition Theorem
V. Arvind Rameshwar, Anshoo Tandon
In this paper, we consider the problem of degradation of anonymity upon linkages of anonymized datasets. We work in the setting where an adversary links together anonymiz…
Bounding User Contributions for User-Level Differentially Private Mean Estimation
V. Arvind Rameshwar, Anshoo Tandon
We revisit the problem of releasing the sample mean of bounded samples in a dataset, privately, under user-level -differential privacy (DP). We aim to derive the optim…
Optimal Tree-Based Mechanisms for Differentially Private Approximate CDFs
V. Arvind Rameshwar, Anshoo Tandon, Abhay Sharma
This paper considers the -differentially private (DP) release of an approximate cumulative distribution function (CDF) of the samples in a dataset. We assume that the…
Enhancing MOTION2NX for Efficient, Scalable and Secure Image Inference using Convolutional Neural Networks
Haritha K, Ramya Burra, Srishti Mittal +3
This work contributes towards the development of an efficient and scalable open-source Secure Multi-Party Computation (SMPC) protocol on machines with moderate computational resour…
On Improving the Composition Privacy Loss in Differential Privacy for Fixed Estimation Error
V. Arvind Rameshwar, Anshoo Tandon
This paper considers the private release of statistics of disjoint subsets of a dataset, in the setting of data heterogeneity, where users could contribute more than one sample, wi…
Mean Estimation with User-Level Privacy for Spatio-Temporal IoT Datasets
V. Arvind Rameshwar, Anshoo Tandon, Prajjwal Gupta +3
This paper considers the problem of the private release of sample means of speed values from traffic datasets. Our key contribution is the development of user-level differentially…