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AdaSTopk: Adaptive federated shuffle model based on differential privacy

Information sciences, 2023-09, Vol.642, p.119186, Article 119186

2023

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RAFLS: RDP-Based Adaptive Federated Learning With Shuffle Model

IEEE transactions on dependable and secure computing, 2024-07, p.1-14

2024

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Distributed Differential Privacy via Shuffling Versus Aggregation: A Curious Study

IEEE transactions on information forensics and security, 2024, Vol.19, p.2501-2516

2024

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Private Summation in the Multi-Message Shuffle Model

Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security, 2020, p.657-676

2020

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Differentially Private Numerical Vector Analyses in the Local and Shuffle Model

IEEE transactions on dependable and secure computing, 2024, p.1-15

2024

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Differentially Private Probabilistic Social Choice in the Shuffle Model

Integrated Uncertainty in Knowledge Modelling and Decision Making, p.37-48

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Differentially Private Histograms in the Shuffle Model from Fake Users

2022 IEEE Symposium on Security and Privacy (SP), 2022, p.440-457

2022

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A Multi-Shuffler Framework to Establish Mutual Confidence for Secure Federated Learning

IEEE transactions on dependable and secure computing, 2023-09, Vol.20 (5), p.4230-4244

2023

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Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy

IEEE transactions on information forensics and security, 2022, Vol.17, p.612-627

2022

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Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022, p.1505-1519

2022

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Rényi Differential Privacy in the Shuffle Model: Enhanced Amplification Bounds

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, p.4590-4594

2024

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Distributed Differentially Private Ranking Aggregation

IEEE transactions on computational social systems, 2024-02, Vol.11 (1), p.1-11

2024

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Joint Top-K Sparsification and Shuffle Model for Communication-Privacy-Accuracy Tradeoffs in Federated-Learning-Based IoV

IEEE internet of things journal, 2024-06, Vol.11 (11), p.19721-19735

2024

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Distributed Differentially Private Ranking Aggregation

Advances in Knowledge Discovery and Data Mining, p.236-248

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The limits of pan privacy and shuffle privacy for learning and estimation

Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021, p.1081-1094

2021

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Analyzing the Shuffle Model Through the Lens of Quantitative Information Flow

2023 IEEE 36th Computer Security Foundations Symposium (CSF), 2023, p.423-438

2023

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Tight Differential Privacy Guarantees for the Shuffle Model with k-Randomized Response

Foundations and Practice of Security, p.440-458

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On the Round Complexity of the Shuffle Model

Theory of Cryptography, 2020, Vol.12551, p.683-712

2020

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The Preservation of Weighted Graphs based on Shuffle differential privacy in Social Networks

2024 International Conference on Networking and Network Applications (NaNA), 2024, p.209-214

2024

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An Uncertain Graph Method based on Shuffle Model to Preserve Link Privacy of Mobile Social Networks

Journal of Information Science and Engineering, 2024-01, Vol.40 (1), p.125-150

2024

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Amplification by Shuffling without Shuffling

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023, p.2292-2305

2023

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AdaSTopk: Adaptive federated shuffle model based on differential privacy

RAFLS: RDP-Based Adaptive Federated Learning With Shuffle Model

Distributed Differential Privacy via Shuffling Versus Aggregation: A Curious Study

Private Summation in the Multi-Message Shuffle Model

Differentially Private Numerical Vector Analyses in the Local and Shuffle Model

Differentially Private Probabilistic Social Choice in the Shuffle Model

Differentially Private Histograms in the Shuffle Model from Fake Users

A Multi-Shuffler Framework to Establish Mutual Confidence for Secure Federated Learning

Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy

Differentially Private Triangle and 4-Cycle Counting in the Shuffle Model

Rényi Differential Privacy in the Shuffle Model: Enhanced Amplification Bounds

Distributed Differentially Private Ranking Aggregation

Joint Top-K Sparsification and Shuffle Model for Communication-Privacy-Accuracy Tradeoffs in Federated-Learning-Based IoV

Distributed Differentially Private Ranking Aggregation

The limits of pan privacy and shuffle privacy for learning and estimation

Analyzing the Shuffle Model Through the Lens of Quantitative Information Flow

Tight Differential Privacy Guarantees for the Shuffle Model with k-Randomized Response

On the Round Complexity of the Shuffle Model

The Preservation of Weighted Graphs based on Shuffle differential privacy in Social Networks

An Uncertain Graph Method based on Shuffle Model to Preserve Link Privacy of Mobile Social Networks

Amplification by Shuffling without Shuffling

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