Copertina

Privacy Amplification via Shuffling: Unified, Simplified, and Tightened

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Shaowei, Peng, Yun, Li, Jin, Wen, Zikai, Li, Zhipeng, Yu, Shiyu, Wang, Di, Yang, Wei
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Cryptography and Security
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Decomposition-Based Optimal Bounds for Privacy Amplification via Shuffling
di: Su, Pengcheng, et al.
Pubblicazione: (2025)

Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling
di: Wang, Shaowei, et al.
Pubblicazione: (2024)

A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility
di: Chen, E, et al.
Pubblicazione: (2023)

RAIN: Secure and Robust Aggregation under Shuffle Model of Differential Privacy
di: Li, Yuhang, et al.
Pubblicazione: (2026)

Segmented Private Data Aggregation in the Multi-message Shuffle Model
di: Wang, Shaowei, et al.
Pubblicazione: (2024)

Robust Single-message Shuffle Differential Privacy Protocol for Accurate Distribution Estimation
di: Li, Xiaoguang, et al.
Pubblicazione: (2026)

Enhanced Privacy Bound for Shuffle Model with Personalized Privacy
di: Liu, Yixuan, et al.
Pubblicazione: (2024)

Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification
di: Schuchardt, Jan, et al.
Pubblicazione: (2024)

CSVAR: Enhancing Visual Privacy in Federated Learning via Adaptive Shuffling Against Overfitting
di: Chen, Zhuo, et al.
Pubblicazione: (2025)

Tight Differential Privacy Guarantees for the Shuffle Model with $k$-Randomized Response
di: Biswas, Sayan, et al.
Pubblicazione: (2022)

Efficient Verifiable Differential Privacy with Input Authenticity in the Local and Shuffle Model
di: Bontekoe, Tariq, et al.
Pubblicazione: (2024)

Privacy Amplification for BandMF via $b$-Min-Sep Subsampling
di: Dong, Andy, et al.
Pubblicazione: (2026)

On the (In-)Security of the Shuffling Defense in the Transformer Secure Inference
di: Li, Zhengyi, et al.
Pubblicazione: (2026)

FPT-Noise: Dynamic Scene-Aware Counterattack for Test-Time Adversarial Defense in Vision-Language Models
di: Deng, Jia, et al.
Pubblicazione: (2025)

Near Exact Privacy Amplification for Matrix Mechanisms
di: Choquette-Choo, Christopher A., et al.
Pubblicazione: (2024)

Personalized Privacy Amplification via Importance Sampling
di: Fay, Dominik, et al.
Pubblicazione: (2023)

Augmented Shuffle Protocols for Accurate and Robust Frequency Estimation under Differential Privacy
di: Murakami, Takao, et al.
Pubblicazione: (2025)

Defense against Poisoning Attacks under Shuffle-DP
di: Wang, Siyi, et al.
Pubblicazione: (2026)

Near-Optimal Reinforcement Learning with Shuffle Differential Privacy
di: Bai, Shaojie, et al.
Pubblicazione: (2024)

Augmented Shuffle Differential Privacy Protocols for Large-Domain Categorical and Key-Value Data
di: Murakami, Takao, et al.
Pubblicazione: (2025)

Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy
di: Xu, Shuangqing, et al.
Pubblicazione: (2024)

Privacy Amplification for the Gaussian Mechanism via Bounded Support
di: Hu, Shengyuan, et al.
Pubblicazione: (2024)

Automatically Tightening Access Control Policies with Restricter
di: Wu, Ka Lok, et al.
Pubblicazione: (2026)

Privacy Amplification for Matrix Mechanisms
di: Choquette-Choo, Christopher A., et al.
Pubblicazione: (2023)

To Shuffle or not to Shuffle: Auditing DP-SGD with Shuffling
di: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Pubblicazione: (2024)

Leveraging Randomness in Model and Data Partitioning for Privacy Amplification
di: Dong, Andy, et al.
Pubblicazione: (2025)

Bayesian Advantage of Re-Identification Attack in the Shuffle Model
di: Su, Pengcheng, et al.
Pubblicazione: (2025)

Shuffling for Semantic Secrecy
di: Chen, Fupei, et al.
Pubblicazione: (2025)

Almost Instance-optimal Clipping for Summation Problems in the Shuffle Model of Differential Privacy
di: Dong, Wei, et al.
Pubblicazione: (2024)

Efficient Fault-Tolerant Quantum Protocol for Differential Privacy in the Shuffle Model
di: Asghar, Hassan Jameel, et al.
Pubblicazione: (2024)

Five Attacks on x402 Agentic Payment Protocol
di: Li, Zelin, et al.
Pubblicazione: (2026)

A Hardware-Friendly Shuffling Countermeasure Against Side-Channel Attacks for Kyber
di: Xu, Dejun, et al.
Pubblicazione: (2024)

A Unified View of IoT And CPS Security and Privacy
di: Luo, Lan, et al.
Pubblicazione: (2022)

Network-Aware Differential Privacy
di: Li, Zhou, et al.
Pubblicazione: (2025)

Mutual Information Bounds in the Shuffle Model
di: Su, Pengcheng, et al.
Pubblicazione: (2025)

Convergent Privacy Framework for Multi-layer GNNs through Contractive Message Passing
di: Zheng, Yu, et al.
Pubblicazione: (2025)

Fed-AugMix: Balancing Privacy and Utility via Data Augmentation
di: Li, Haoyang, et al.
Pubblicazione: (2024)

Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration
di: Pierquin, Clément, et al.
Pubblicazione: (2023)

Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run
di: Xiang, Zihang, et al.
Pubblicazione: (2025)

Privacy-preserving Quantification of Non-IID Degree in Federated Learning
di: Yan, Yuping, et al.
Pubblicazione: (2024)