One-shot Empirical Privacy Estimation for Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Andrew, Galen, Kairouz, Peter, Oh, Sewoong, Oprea, Alina, McMahan, H. Brendan, Suriyakumar, Vinith M. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Federated Learning in Practice: Reflections and Projections
by: Daly, Katharine, et al.
Published: (2024)
by: Daly, Katharine, et al.
Published: (2024)
An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy
by: McMahan, H. Brendan, et al.
Published: (2025)
by: McMahan, H. Brendan, et al.
Published: (2025)
Privacy-Preserving Instructions for Aligning Large Language Models
by: Yu, Da, et al.
Published: (2024)
by: Yu, Da, et al.
Published: (2024)
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
by: Chen, Wei-Ning, et al.
Published: (2024)
by: Chen, Wei-Ning, et al.
Published: (2024)
Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning
by: Ball, Marshall, et al.
Published: (2024)
by: Ball, Marshall, et al.
Published: (2024)
On Design Principles for Private Adaptive Optimizers
by: Ganesh, Arun, et al.
Published: (2025)
by: Ganesh, Arun, et al.
Published: (2025)
Randomization Techniques to Mitigate the Risk of Copyright Infringement
by: Chen, Wei-Ning, et al.
Published: (2024)
by: Chen, Wei-Ning, et al.
Published: (2024)
Hush! Protecting Secrets During Model Training: An Indistinguishability Approach
by: Ganesh, Arun, et al.
Published: (2025)
by: Ganesh, Arun, et al.
Published: (2025)
How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy
by: Ponomareva, Natalia, et al.
Published: (2025)
by: Ponomareva, Natalia, et al.
Published: (2025)
UCD: Unlearning in LLMs via Contrastive Decoding
by: Suriyakumar, Vinith M., et al.
Published: (2025)
by: Suriyakumar, Vinith M., et al.
Published: (2025)
Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy
by: Dvijotham, Krishnamurthy, et al.
Published: (2024)
by: Dvijotham, Krishnamurthy, et al.
Published: (2024)
Confidential Federated Computations
by: Eichner, Hubert, et al.
Published: (2024)
by: Eichner, Hubert, et al.
Published: (2024)
AirGapAgent: Protecting Privacy-Conscious Conversational Agents
by: Bagdasarian, Eugene, et al.
Published: (2024)
by: Bagdasarian, Eugene, et al.
Published: (2024)
Synthesizing Tight Privacy and Accuracy Bounds via Weighted Model Counting
by: Oakley, Lisa, et al.
Published: (2024)
by: Oakley, Lisa, et al.
Published: (2024)
Fine-Tuning Large Language Models with User-Level Differential Privacy
by: Charles, Zachary, et al.
Published: (2024)
by: Charles, Zachary, et al.
Published: (2024)
User Inference Attacks on Large Language Models
by: Kandpal, Nikhil, et al.
Published: (2023)
by: Kandpal, Nikhil, et al.
Published: (2023)
Backdoor Attacks in Peer-to-Peer Federated Learning
by: Syros, Georgios, et al.
Published: (2023)
by: Syros, Georgios, et al.
Published: (2023)
Black-Box Privacy Attacks on Shared Representations in Multitask Learning
by: Abascal, John, et al.
Published: (2025)
by: Abascal, John, et al.
Published: (2025)
Optimal Attack and Defense for Reinforcement Learning
by: McMahan, Jeremy, et al.
Published: (2023)
by: McMahan, Jeremy, et al.
Published: (2023)
Adversarial Inception Backdoor Attacks against Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2024)
by: Rathbun, Ethan, et al.
Published: (2024)
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
by: Rathbun, Ethan, et al.
Published: (2024)
by: Rathbun, Ethan, et al.
Published: (2024)
Releasing Large-Scale Human Mobility Histograms with Differential Privacy
by: Bian, Christopher, et al.
Published: (2024)
by: Bian, Christopher, et al.
Published: (2024)
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models
by: Suriyakumar, Vinith M., et al.
Published: (2024)
by: Suriyakumar, Vinith M., et al.
Published: (2024)
Toward a Principled Framework for Agent Safety Measurement
by: Lin, Shuyi, et al.
Published: (2026)
by: Lin, Shuyi, et al.
Published: (2026)
Reconstruction of Personally Identifiable Information from Supervised Finetuned Models
by: Furukawa, Sae, et al.
Published: (2026)
by: Furukawa, Sae, et al.
Published: (2026)
Correlated Noise Mechanisms for Differentially Private Learning
by: Pillutla, Krishna, et al.
Published: (2025)
by: Pillutla, Krishna, et al.
Published: (2025)
Privacy in Federated Learning
by: Sen, Jaydip, et al.
Published: (2024)
by: Sen, Jaydip, et al.
Published: (2024)
Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment
by: Cummings, Rachel, et al.
Published: (2023)
by: Cummings, Rachel, et al.
Published: (2023)
Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning
by: Chen, Chaoran, et al.
Published: (2026)
by: Chen, Chaoran, et al.
Published: (2026)
Belt and Braces: When Federated Learning Meets Differential Privacy
by: Ren, Xuebin, et al.
Published: (2024)
by: Ren, Xuebin, et al.
Published: (2024)
DROP: Poison Dilution via Knowledge Distillation for Federated Learning
by: Syros, Georgios, et al.
Published: (2025)
by: Syros, Georgios, et al.
Published: (2025)
Beware Untrusted Simulators -- Reward-Free Backdoor Attacks in Reinforcement Learning
by: Rathbun, Ethan, et al.
Published: (2026)
by: Rathbun, Ethan, et al.
Published: (2026)
TMI! Finetuned Models Leak Private Information from their Pretraining Data
by: Abascal, John, et al.
Published: (2023)
by: Abascal, John, et al.
Published: (2023)
CLIOPATRA: Extracting Private Information from LLM Insights
by: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Published: (2026)
by: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Published: (2026)
Syntax- and Compilation-Preserving Evasion of LLM Vulnerability Detectors
by: Sun, Luze, et al.
Published: (2026)
by: Sun, Luze, et al.
Published: (2026)
Inception: Efficiently Computable Misinformation Attacks on Markov Games
by: McMahan, Jeremy, et al.
Published: (2024)
by: McMahan, Jeremy, et al.
Published: (2024)
Federated Learning-Enhanced Blockchain Framework for Privacy-Preserving Intrusion Detection in Industrial IoT
by: Ali, Anas, et al.
Published: (2025)
by: Ali, Anas, et al.
Published: (2025)
Privacy-Aware Cyberterrorism Network Analysis using Graph Neural Networks and Federated Learning
by: Ali, Anas, et al.
Published: (2025)
by: Ali, Anas, et al.
Published: (2025)
UTrace: Poisoning Forensics for Private Collaborative Learning
by: Rose, Evan, et al.
Published: (2024)
by: Rose, Evan, et al.
Published: (2024)
PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defense
by: Cadet, Xavier, et al.
Published: (2025)
by: Cadet, Xavier, et al.
Published: (2025)
Similar Items
-
Federated Learning in Practice: Reflections and Projections
by: Daly, Katharine, et al.
Published: (2024) -
An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy
by: McMahan, H. Brendan, et al.
Published: (2025) -
Privacy-Preserving Instructions for Aligning Large Language Models
by: Yu, Da, et al.
Published: (2024) -
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
by: Chen, Wei-Ning, et al.
Published: (2024) -
Secure Stateful Aggregation: A Practical Protocol with Applications in Differentially-Private Federated Learning
by: Ball, Marshall, et al.
Published: (2024)