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20242026
most citedConfidential Federated Computations

3 citations · 4 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CR2026

Text-Based Personas for Simulating User Privacy Decisions

Kassem Fawaz, Ren Yi, Octavian Suciu +4

The ability to simulate human privacy decisions has significant implications for aligning autonomous agents with individual intent and conducting cost-effective, large-scale privac…

cs.CR2025

Personalizing Agent Privacy Decisions via Logical Entailment

James Flemings, Ren Yi, Octavian Suciu +3

Personal large language model (LLM) agents increasingly perform tasks that require access to user data, raising concerns about appropriate data disclosure. We show that relying sol…

cs.CR2025

Toward provably private analytics and insights into GenAI use

Albert Cheu, Artem Lagzdin, Brett McLarnon +8

Large-scale systems that compute analytics over a fleet of devices must achieve high privacy and security standards while also meeting data quality, usability, and resource efficie…

cs.CR2024

Mayfly: Private Aggregate Insights from Ephemeral Streams of On-Device User Data

Christopher Bian, Albert Cheu, Stanislav Chiknavaryan +12

This paper introduces Mayfly, a federated analytics approach enabling aggregate queries over ephemeral on-device data streams without central persistence of sensitive user data. Ma…

cs.CR2024

Releasing Large-Scale Human Mobility Histograms with Differential Privacy

Christopher Bian, Albert Cheu, Yannis Guzman +4

Environmental Insights Explorer (EIE) is a Google product that reports aggregate statistics about human mobility, including various methods of transit used by people across roughly…

cs.CR2024★ 1 cited

AirGapAgent: Protecting Privacy-Conscious Conversational Agents

Eugene Bagdasarian, Ren Yi, Sahra Ghalebikesabi +5

The growing use of large language model (LLM)-based conversational agents to manage sensitive user data raises significant privacy concerns. While these agents excel at understandi…

cs.CR2024★ 3 cited

Confidential Federated Computations

Hubert Eichner, Daniel Ramage, Kallista Bonawitz +11

Federated Learning and Analytics (FLA) have seen widespread adoption by technology platforms for processing sensitive on-device data. However, basic FLA systems have privacy limita…