37 citations · 70 across the 3 of their papers we have counts for
4 papers
Libertas: Privacy-Preserving Collective Computation for Decentralised Personal Data Stores
Rui Zhao, Naman Goel, Nitin Agrawal +7
Data and data processing have become an indispensable aspect for our society. Insights drawn from collective data make invaluable contribution to scientific and societal research a…
MPC-Friendly Commitments for Publicly Verifiable Covert Security
Nitin Agrawal, James Bell, Adrià Gascón +1
We address the problem of efficiently verifying a commitment in a two-party computation. This addresses the scenario where a party P1 commits to a value to be used in a subsequ…
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Nitin Agrawal, Reuben Binns, Max Van Kleek +2
Homomorphic encryption, secure multi-party computation, and differential privacy are part of an emerging class of Privacy Enhancing Technologies which share a common promise: to pr…
QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner +1
Recently, there has been a wealth of effort devoted to the design of secure protocols for machine learning tasks. Much of this is aimed at enabling secure prediction from highly-ac…