18 citations · 42 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models
Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha
Directed graphical models (DGMs) are a class of probabilistic models that are widely used for predictive analysis in sensitive domains, such as medical diagnostics. In this paper w…