activity
20192022
most citedRobustness of Locally Differentially Private Graph Analysis Against Poisoning

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing cs.CRShow all

5 papers · 1 filter

cs.CR2022★ 1 cited

Robustness of Locally Differentially Private Graph Analysis Against Poisoning

Jacob Imola, Amrita Roy Chowdhury, Kamalika Chaudhuri

Locally differentially private (LDP) graph analysis allows private analysis on a graph that is distributed across multiple users. However, such computations are vulnerable to data…

cs.CR2021

EIFFeL: Ensuring Integrity for Federated Learning

Amrita Roy Chowdhury, Chuan Guo, Somesh Jha +1

Federated learning (FL) enables clients to collaborate with a server to train a machine learning model. To ensure privacy, the server performs secure aggregation of updates from th…

cs.CR2020

Data Privacy in Trigger-Action Systems

Yunang Chen, Amrita Roy Chowdhury, Ruizhe Wang +3

Trigger-action platforms (TAPs) allow users to connect independent web-based or IoT services to achieve useful automation. They provide a simple interface that helps end-users crea…

cs.CR2020

Strengthening Order Preserving Encryption with Differential Privacy

Amrita Roy Chowdhury, Bolin Ding, Somesh Jha +2

Ciphertexts of an order-preserving encryption (OPE) scheme preserve the order of their corresponding plaintexts. However, OPEs are vulnerable to inference attacks that exploit this…

cs.CR2019

Preech: A System for Privacy-Preserving Speech Transcription

Shimaa Ahmed, Amrita Roy Chowdhury, Kassem Fawaz +1

New Advances in machine learning have made Automated Speech Recognition (ASR) systems practical and more scalable. These systems, however, pose serious privacy threats as speech is…