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Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity

https://doi.org/10.1137/1.9781611975482.151

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11681878_14openalex-snapshot

Calibrating Noise to Sensitivity in Private Data Analysis

inferredcites →https://doi.org/10.1007/11761679_29openalex-snapshot

Our Data, Ourselves: Privacy Via Distributed Noise Generation

inferredcites →https://doi.org/10.1007/11787006_1openalex-snapshot

Differential Privacy

inferredcites →https://doi.org/10.1007/978-3-662-53641-4_24openalex-snapshot

Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds

inferredcites →https://doi.org/10.1080/01621459.1965.10480775openalex-snapshot

Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias

inferredcites →https://doi.org/10.1109/csf.2017.11openalex-snapshot

Rényi Differential Privacy

inferredcites →https://doi.org/10.1109/focs.2008.27openalex-snapshot

What Can We Learn Privately?

inferredcites →https://doi.org/10.1109/focs.2010.12openalex-snapshot

Boosting and Differential Privacy

inferredcites →https://doi.org/10.1109/focs.2014.56openalex-snapshot

Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds

inferredcites →https://doi.org/10.1109/focs.2018.00056openalex-snapshot

Privacy Amplification by Iteration

inferredcites →https://doi.org/10.1109/tkde.2010.247openalex-snapshot

Differential Privacy via Wavelet Transforms

inferredcites →https://doi.org/10.1145/1806689.1806787openalex-snapshot

Differential privacy under continual observation

inferredcites →https://doi.org/10.1145/2043621.2043626openalex-snapshot

Private and Continual Release of Statistics

inferredcites →https://doi.org/10.1145/2815400.2815417openalex-snapshot

Vuvuzela

inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot

Deep Learning with Differential Privacy

inferredcites →https://doi.org/10.1145/2976749.2978409openalex-snapshot

Heavy Hitter Estimation over Set-Valued Data with Local Differential Privacy

inferredcites →https://doi.org/10.1145/3132747.3132783openalex-snapshot

Stadium

inferredcites →https://doi.org/10.1146/annurev-statistics-060116-054123openalex-snapshot

Exposed! A Survey of Attacks on Private Data

inferredcites →https://doi.org/10.1515/popets-2016-0015openalex-snapshot

Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries

inferredcites →https://doi.org/10.1561/9781601988195openalex-snapshot

The Algorithmic Foundations of Differential Privacy

inferredcites →https://doi.org/10.21236/ada465464openalex-snapshot

Tor: The Second-Generation Onion Router

inferredcites →https://doi.org/10.29012/jpc.718openalex-snapshot

Local Differential Privacy for Evolving Data

inferredcites →https://doi.org/10.48550/arxiv.1703.06255openalex-snapshot

Prio: Private, Robust, and Scalable Computation of Aggregate Statistics

inferredcites →https://doi.org/10.48550/arxiv.1709.02753openalex-snapshot

Privacy Loss in Apple's Implementation of Differential Privacy on MacOS 10.12

inferredcites →https://doi.org/10.48550/arxiv.1807.01647openalex-snapshot

Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences

inferredcites →https://doi.org/10.5325/jmodeperistud.5.1.0027openalex-snapshot

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Fedrti: Differential Privacy Federated Learning Via Random Participation and Time Constraints for Network Congestion

inferred← citeshttps://doi.org/10.1002/cpe.7565openalex-snapshot

Differential privacy: Review of improving utility through cryptography‐based technologies

inferred← citeshttps://doi.org/10.1002/cpe.7572openalex-snapshot

SPoFC: A framework for stream data aggregation with local differential privacy

inferred← citeshttps://doi.org/10.1002/cpe.8084openalex-snapshot

Privacy preserving and secure robust federated learning: A survey

inferred← citeshttps://doi.org/10.1002/ett.70490openalex-snapshot

Privacy‐Aware Microgrid Networks With Federated Data Analytics

inferred← citeshttps://doi.org/10.1007/978-3-030-17653-2_13openalex-snapshot

Distributed Differential Privacy via Shuffling

inferred← citeshttps://doi.org/10.1007/978-3-030-26951-7_22openalex-snapshot

The Privacy Blanket of the Shuffle Model

inferred← citeshttps://doi.org/10.1007/978-3-030-45724-2_27openalex-snapshot

Private Aggregation from Fewer Anonymous Messages

inferred← citeshttps://doi.org/10.1007/978-3-030-64378-2_24openalex-snapshot

On the Round Complexity of the Shuffle Model

inferred← citeshttps://doi.org/10.1007/978-3-030-65965-3_33openalex-snapshot

Interpretable Privacy with Optimizable Utility

inferred← citeshttps://doi.org/10.1007/978-3-030-74717-6_1openalex-snapshot

A Post-processing Trajectory Publication Method Under Differential Privacy

inferred← citeshttps://doi.org/10.1007/978-3-030-77883-5_16openalex-snapshot

On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy

inferred← citeshttps://doi.org/10.1007/978-3-030-77883-5_17openalex-snapshot

Non-Interactive Anonymous Router

inferred← citeshttps://doi.org/10.1007/978-3-030-81242-3_2openalex-snapshot

Comparing Local and Central Differential Privacy Using Membership Inference Attacks

inferred← citeshttps://doi.org/10.1007/978-3-030-85529-1_21openalex-snapshot

Fairly Private Through Group Tagging and Relation Impact

inferred← citeshttps://doi.org/10.1007/978-3-030-86520-7_49openalex-snapshot

Privacy Amplification via Iteration for Shuffled and Online PNSGD

inferred← citeshttps://doi.org/10.1007/978-3-031-06761-7_48openalex-snapshot

Optimization Design of Privacy Protection System Based on Cloud Native

inferred← citeshttps://doi.org/10.1007/978-3-031-09234-3_25openalex-snapshot

Spreading the Privacy Blanket:

inferred← citeshttps://doi.org/10.1007/978-3-031-14791-3_6openalex-snapshot

Approximate Distance-Comparison-Preserving Symmetric Encryption

inferred← citeshttps://doi.org/10.1007/978-3-031-20974-1_16openalex-snapshot

ACDC: Anonymous Crowdsourcing Using Digital Cash

inferred← citeshttps://doi.org/10.1007/978-3-031-30620-4_1openalex-snapshot

A Theory of Composition for Differential Obliviousness

inferred← citeshttps://doi.org/10.1007/978-3-031-30637-2_20openalex-snapshot

Accurate and Efficient Trajectory-Based Contact Tracing with Secure Computation and Geo-Indistinguishability

inferred← citeshttps://doi.org/10.1007/978-3-031-34896-9_20openalex-snapshot

A Review of Federated Learning: Algorithms, Frameworks and Applications

inferred← citeshttps://doi.org/10.1007/978-3-031-38545-2_20openalex-snapshot

PAC Privacy: Automatic Privacy Measurement and Control of Data Processing

inferred← citeshttps://doi.org/10.1007/978-3-031-39847-6_10openalex-snapshot

PrivSketch: A Private Sketch-Based Frequency Estimation Protocol for Data Streams

inferred← citeshttps://doi.org/10.1007/978-3-031-46775-2_4openalex-snapshot

Differentially Private Probabilistic Social Choice in the Shuffle Model

inferred← citeshttps://doi.org/10.1007/978-3-031-48621-0_3openalex-snapshot

Non-Interactive Anonymous Router with Quasi-Linear Router Computation

inferred← citeshttps://doi.org/10.1007/978-3-031-57537-2_27openalex-snapshot

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

inferred← citeshttps://doi.org/10.1007/978-3-031-60391-4_11openalex-snapshot

Privacy Preserving Federated Learning: A Novel Approach for Combining Differential Privacy and Homomorphic Encryption

inferred← citeshttps://doi.org/10.1007/978-3-031-68397-8_3openalex-snapshot

MPC for Tech Giants (GMPC): Enabling Gulliver and the Lilliputians to Cooperate Amicably

inferred← citeshttps://doi.org/10.1007/978-3-031-70890-9_20openalex-snapshot

Exploiting Internal Randomness for Privacy in Vertical Federated Learning

inferred← citeshttps://doi.org/10.1007/978-3-032-00891-6_13openalex-snapshot

Differential Private Risk Factors Analysis of Polypharmacy

inferred← citeshttps://doi.org/10.1007/978-3-032-26734-4_11openalex-snapshot

Secret-Shared Shuffle from Authenticated Correlations

inferred← citeshttps://doi.org/10.1007/978-3-032-33260-8_3openalex-snapshot

IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning

inferred← citeshttps://doi.org/10.1007/978-981-95-5787-5_6openalex-snapshot

Hybrid Differential Privacy

inferred← citeshttps://doi.org/10.1007/978-981-96-3774-4_10openalex-snapshot

Secure Aggregation of Smartwatch Health Data with LDP

inferred← citeshttps://doi.org/10.1007/978-981-97-0407-1_7openalex-snapshot

Advances in Differential Privacy and Differentially Private Machine Learning

inferred← citeshttps://doi.org/10.1007/978-981-97-1332-5_17openalex-snapshot

Data Stream Aggregation Mechanism Under Local Differential Privacy

inferred← citeshttps://doi.org/10.1007/978-981-99-9614-8_8openalex-snapshot

Toward the Tradeoffs Between Privacy, Fairness and Utility in Federated Learning

inferred← citeshttps://doi.org/10.1007/978-981-99-9785-5_33openalex-snapshot

Personalized Differential Privacy in the Shuffle Model

inferred← citeshttps://doi.org/10.1007/s00778-022-00728-2openalex-snapshot

Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms

inferred← citeshttps://doi.org/10.1007/s10114-025-2679-7openalex-snapshot

Privacy-Preserving Federated Averaging on Heterogeneous Data

inferred← citeshttps://doi.org/10.1007/s10255-024-1095-6openalex-snapshot

Privacy-Preserving Frank-Wolfe on Shuffle Model

inferred← citeshttps://doi.org/10.1007/s10994-022-06267-9openalex-snapshot

An accurate, scalable and verifiable protocol for federated differentially private averaging

inferred← citeshttps://doi.org/10.1007/s11227-023-05378-xopenalex-snapshot

Local differentially private federated learning with homomorphic encryption

inferred← citeshttps://doi.org/10.1007/s11390-023-1346-7openalex-snapshot

Hadamard Encoding Based Frequent Itemset Mining under Local Differential Privacy

inferred← citeshttps://doi.org/10.1007/s11704-021-0412-yopenalex-snapshot

Efficient protocols for heavy hitter identification with local differential privacy

inferred← citeshttps://doi.org/10.1007/s42979-019-0023-yopenalex-snapshot

ARA: Aggregated RAPPOR and Analysis for Centralized Differential Privacy

inferred← citeshttps://doi.org/10.1007/s44443-025-00397-5openalex-snapshot

AdaCOS: adaptive differential privacy shuffle model based on cosine similarity

inferred← citeshttps://doi.org/10.1007/s44443-026-00510-2openalex-snapshot

Review on federated optimization in multi-tier architectures

inferred← citeshttps://doi.org/10.1016/j.adhoc.2026.104205openalex-snapshot

A review of privacy-aware blockchain architectures for vehicular energy trading networks

inferred← citeshttps://doi.org/10.1016/j.comcom.2024.06.009openalex-snapshot

Hybrid aggregation for federated learning under blockchain framework

inferred← citeshttps://doi.org/10.1016/j.comnet.2024.110830openalex-snapshot

Local Differential Privacy for correlated location data release in ITS

inferred← citeshttps://doi.org/10.1016/j.future.2025.107706openalex-snapshot

FedShufde: A privacy preserving framework of federated learning for edge-based smart UAV delivery system

inferred← citeshttps://doi.org/10.1016/j.is.2026.102726openalex-snapshot

The use of differential privacy for privacy-preserving record linkage: Protecting the bits but not the people

inferred← citeshttps://doi.org/10.1016/j.tcs.2025.115492openalex-snapshot

Visualizing differentially private mechanisms with physical cards

inferred← citeshttps://doi.org/10.1038/s41598-026-38537-0openalex-snapshot

Tighter privacy auditing of differentially private stochastic gradient descent in the hidden state threat model

inferred← citeshttps://doi.org/10.1049/icp.2022.2041openalex-snapshot

Tight differential privacy blanket for shuff model

inferred← citeshttps://doi.org/10.1109/2575-8411.2026.00040openalex-snapshot

Multi-Shuffler: Decentralized Shuffling for Differential Privacy in Mobile Edge Computing

inferred← citeshttps://doi.org/10.1109/access.2020.2990296openalex-snapshot

Associated Attribute-Aware Differentially Private Data Publishing via Microaggregation

inferred← citeshttps://doi.org/10.1109/access.2022.3204037openalex-snapshot

A Survey and Guideline on Privacy Enhancing Technologies for Collaborative Machine Learning

inferred← citeshttps://doi.org/10.1109/access.2022.3208715openalex-snapshot

Machine Learning Model Generation With Copula-Based Synthetic Dataset for Local Differentially Private Numerical Data

inferred← citeshttps://doi.org/10.1109/aibthings63359.2024.10863022openalex-snapshot

Privacy Preservation Techniques in Smart Grids: Balancing Security and Utility in IoT-Driven Environments

inferred← citeshttps://doi.org/10.1109/asiancomnet68615.2025.11579615openalex-snapshot

Optimizing Differential Privacy: The Role of Model Parallelism and Iteration Subsampling

inferred← citeshttps://doi.org/10.1109/bigdata55660.2022.10020232openalex-snapshot

FL-Market: Trading Private Models in Federated Learning

inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10826023openalex-snapshot

Hierarchical Federated Learning with Privacy

inferred← citeshttps://doi.org/10.1109/cic56439.2022.00013openalex-snapshot

Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks

inferred← citeshttps://doi.org/10.1109/csf57540.2023.00033openalex-snapshot

Analyzing the Shuffle Model Through the Lens of Quantitative Information Flow

inferred← citeshttps://doi.org/10.1109/csf57540.2023.00034openalex-snapshot

From Bounded to Unbounded: Privacy Amplification via Shuffling with Dummies

inferred← citeshttps://doi.org/10.1109/csf68417.2026.00020openalex-snapshot

Setup Protocols for Sender Anonymity

inferred← citeshttps://doi.org/10.1109/eurosp57164.2023.00023openalex-snapshot

Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation

inferred← citeshttps://doi.org/10.1109/focs.2019.00015openalex-snapshot

The Role of Interactivity in Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/focs52979.2021.00096openalex-snapshot

Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling

inferred← citeshttps://doi.org/10.1109/globecom59602.2025.11432410openalex-snapshot

Non-interactive Triangle Counting with Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/hpcc64274.2024.00074openalex-snapshot

FAdagrad: Adaptive federated learning with differential privacy

inferred← citeshttps://doi.org/10.1109/ic-rvitm60032.2023.10435015openalex-snapshot

Impact of Additive noise on Information loss characteristics of datasets

inferred← citeshttps://doi.org/10.1109/ic-rvitm60032.2023.10435304openalex-snapshot

Impact of Multiplicative noise on Information loss characteristics of datasets

inferred← citeshttps://doi.org/10.1109/icassp43922.2022.9746975openalex-snapshot

An Efficient DP-SGD Mechanism for Large Scale NLU Models

inferred← citeshttps://doi.org/10.1109/icassp48485.2024.10446115openalex-snapshot

Rényi Differential Privacy in the Shuffle Model: Enhanced Amplification Bounds

inferred← citeshttps://doi.org/10.1109/icbaie49996.2020.00054openalex-snapshot

Differential Privacy Information Publishing Algorithm based on Cluster Anonymity

inferred← citeshttps://doi.org/10.1109/icc52391.2025.11161705openalex-snapshot

Non-Interactive Butterfly Counting in Bipartite Graphs Based on Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/icccnt49239.2020.9225470openalex-snapshot

BUDS: Balancing Utility and Differential Privacy by Shuffling

inferred← citeshttps://doi.org/10.1109/icccs69761.2026.11613418openalex-snapshot

Privacy Amplification via Random Client Check-Ins and Data Subsampling in Federated Learning

inferred← citeshttps://doi.org/10.1109/icde60146.2024.00137openalex-snapshot

Real-Time Trajectory Synthesis with Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/icde65448.2025.00161openalex-snapshot

Towards Learning on Vertically Partitioned Data with Distributed Differential Privacy

inferred← citeshttps://doi.org/10.1109/icde65448.2025.00263openalex-snapshot

Dual Utilization of Perturbation for Stream Data Publication Under Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/icdew58674.2023.00026openalex-snapshot

Locally Private Streaming Data Release with Shuffling and Subsampling

inferred← citeshttps://doi.org/10.1109/iciea58696.2023.10241529openalex-snapshot

Shuffled Differentially Private Federated Learning for Time Series Data Analytics

inferred← citeshttps://doi.org/10.1109/ijcnn48605.2020.9207618openalex-snapshot

Lightweight Crypto-Assisted Distributed Differential Privacy for Privacy-Preserving Distributed Learning

inferred← citeshttps://doi.org/10.1109/infocom52122.2024.10621194openalex-snapshot

Optimal Locally Private Data Stream Analytics

inferred← citeshttps://doi.org/10.1109/infocom53939.2023.10229063openalex-snapshot

Stateful Switch: Optimized Time Series Release with Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/isit45174.2021.9517906openalex-snapshot

Differentially Private Federated Learning with Shuffling and Client Self-Sampling

inferred← citeshttps://doi.org/10.1109/isit50566.2022.9834713openalex-snapshot

Distributed User-Level Private Mean Estimation

inferred← citeshttps://doi.org/10.1109/ispa67752.2025.00106openalex-snapshot

Dynamic Private Subnetwork Selection for Personalized Federated Learning

inferred← citeshttps://doi.org/10.1109/itw54588.2022.9965815openalex-snapshot

Private Federated Submodel Learning with Sparsification

inferred← citeshttps://doi.org/10.1109/itw54588.2022.9965898openalex-snapshot

Straggler-Resilient Differentially-Private Decentralized Learning

inferred← citeshttps://doi.org/10.1109/jiot.2022.3153043openalex-snapshot

Smart Meter Data Obfuscation With a Hybrid Privacy-Preserving Data Publishing Scheme Without a Trusted Third Party

inferred← citeshttps://doi.org/10.1109/jiot.2023.3267082openalex-snapshot

Automatic Tuning of Privacy Budgets in Input-Discriminative Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/jiot.2023.3312852openalex-snapshot

Differentially Private Federated Clustering Over Non-IID Data

inferred← citeshttps://doi.org/10.1109/jiot.2024.3370991openalex-snapshot

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

inferred← citeshttps://doi.org/10.1109/jiot.2024.3376552openalex-snapshot

Privacy-Preserving Federated Primal—Dual Learning for Nonconvex and Nonsmooth Problems With Model Sparsification

inferred← citeshttps://doi.org/10.1109/jiot.2024.3397908openalex-snapshot

Streaming Data Collection With a Private Sketch-Based Protocol

inferred← citeshttps://doi.org/10.1109/jsac.2021.3118408openalex-snapshot

Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation

inferred← citeshttps://doi.org/10.1109/jsac.2022.3142358openalex-snapshot

Private Retrieval, Computing, and Learning: Recent Progress and Future Challenges

inferred← citeshttps://doi.org/10.1109/jsait.2021.3056102openalex-snapshot

Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs

inferred← citeshttps://doi.org/10.1109/jsait.2024.3366225openalex-snapshot

Multi-Message Shuffled Privacy in Federated Learning

inferred← citeshttps://doi.org/10.1109/jsait.2024.3389954openalex-snapshot

Differentially Private Stochastic Linear Bandits: (Almost) for Free

inferred← citeshttps://doi.org/10.1109/jsait.2024.3397305openalex-snapshot

Contraction of Locally Differentially Private Mechanisms

inferred← citeshttps://doi.org/10.1109/jsait.2024.3400995openalex-snapshot

Straggler-Resilient Differentially Private Decentralized Learning

inferred← citeshttps://doi.org/10.1109/lnet.2021.3094518openalex-snapshot

Preserving User Privacy in Personalized Networks

inferred← citeshttps://doi.org/10.1109/mnet.001.2200204openalex-snapshot

Differentially Private Federated Learning in Edge Networks: The Perspective of Noise Reduction

inferred← citeshttps://doi.org/10.1109/ojits.2024.3440876openalex-snapshot

A Secure Object Detection Technique for Intelligent Transportation Systems

inferred← citeshttps://doi.org/10.1109/satml59370.2024.00030openalex-snapshot

Differentially Private Multi-Site Treatment Effect Estimation

inferred← citeshttps://doi.org/10.1109/satml59370.2024.00032openalex-snapshot

Differentially Private Heavy Hitter Detection using Federated Analytics

inferred← citeshttps://doi.org/10.1109/satml64287.2025.00039openalex-snapshot

Correlated Privacy Mechanisms for Differentially Private Distributed Mean Estimation

inferred← citeshttps://doi.org/10.1109/sp40000.2020.00037openalex-snapshot

Path Oblivious Heap: Optimal and Practical Oblivious Priority Queue

inferred← citeshttps://doi.org/10.1109/sp40001.2021.00001openalex-snapshot

Manipulation Attacks in Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/sp61157.2025.00019openalex-snapshot

Augmented Shuffle Protocols for Accurate and Robust Frequency Estimation Under Differential Privacy

inferred← citeshttps://doi.org/10.1109/sp61157.2025.00255openalex-snapshot

An Attack-Agnostic Defense Framework Against Manipulation Attacks Under Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/sp63933.2026.00234openalex-snapshot

Sparse Estimation Under Local Differential Privacy at All Privacy Levels

inferred← citeshttps://doi.org/10.1109/tcc.2026.3680131openalex-snapshot

SSDP-DCA: Enhancing Data Collaboration Analysis With Privacy Amplification Techniques in Cloud Environments

inferred← citeshttps://doi.org/10.1109/tcss.2026.3693692openalex-snapshot

Textless, Tiny, and Private: Hashed n-Grams With LLM-Teacher Distillation and Local Differential Privacy for Mental-Health Screening on Social Media

inferred← citeshttps://doi.org/10.1109/tdsc.2019.2927695openalex-snapshot

Locally Differentially Private Heavy Hitter Identification

inferred← citeshttps://doi.org/10.1109/tdsc.2022.3174887openalex-snapshot

Privacy-Preserving Collaborative Data Collection and Analysis with Many Missing Values

inferred← citeshttps://doi.org/10.1109/tdsc.2022.3215574openalex-snapshot

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

inferred← citeshttps://doi.org/10.1109/tdsc.2022.3227568openalex-snapshot

Efficient Noise Generation Protocols for Differentially Private Multiparty Computation

inferred← citeshttps://doi.org/10.1109/tdsc.2023.3263162openalex-snapshot

Privacy Enhancement Via Dummy Points in the Shuffle Model

inferred← citeshttps://doi.org/10.1109/tdsc.2023.3340178openalex-snapshot

Differentially Private Numerical Vector Analyses in the Local and Shuffle Model

inferred← citeshttps://doi.org/10.1109/tdsc.2025.3626847openalex-snapshot

Blockchain-Based Secure Federated Learning With Improved Consensus Protocol and Personalized Differential Privacy

inferred← citeshttps://doi.org/10.1109/tdsc.2025.3636189openalex-snapshot

RATR: Optimized Trajectory Release With Temporal Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/tdsc.2026.3694826openalex-snapshot

SilentNoise: Non-Interactive Noise Generation for Differential Privacy With Malicious Security

inferred← citeshttps://doi.org/10.1109/tifs.2024.3351474openalex-snapshot

Distributed Differential Privacy via Shuffling Versus Aggregation: A Curious Study

inferred← citeshttps://doi.org/10.1109/tifs.2024.3405183openalex-snapshot

Shuffle Private Decentralized Convex Optimization

inferred← citeshttps://doi.org/10.1109/tifs.2024.3480712openalex-snapshot

Generating Location Traces With Semantic- Constrained Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/tifs.2025.3571661openalex-snapshot

Side-Channel Attacks and New Principles in the Shuffle Model of Differential Privacy

inferred← citeshttps://doi.org/10.1109/tifs.2025.3611126openalex-snapshot

UDFed: A Universal Defense Scheme for Various Poisoning Attacks on Federated Learning

inferred← citeshttps://doi.org/10.1109/tit.2019.2922628openalex-snapshot

Anonymous Heterogeneous Distributed Detection: Optimal Decision Rules, Error Exponents, and the Price of Anonymity

inferred← citeshttps://doi.org/10.1109/tit.2020.2985059openalex-snapshot

Privacy of Dependent Users Against Statistical Matching

inferred← citeshttps://doi.org/10.1109/tit.2021.3049802openalex-snapshot

Private Hypothesis Selection

inferred← citeshttps://doi.org/10.1109/tit.2022.3218772openalex-snapshot

Breaking the Communication-Privacy-Accuracy Trilemma

inferred← citeshttps://doi.org/10.1109/tit.2023.3292187openalex-snapshot

Private Read Update Write (PRUW) in Federated Submodel Learning (FSL): Communication Efficient Schemes With and Without Sparsification

inferred← citeshttps://doi.org/10.1109/tit.2023.3339450openalex-snapshot

Private Read-Update-Write With Controllable Information Leakage for Storage-Efficient Federated Learning With Top r Sparsification

inferred← citeshttps://doi.org/10.1109/tkde.2022.3177721openalex-snapshot

DDRM: A Continual Frequency Estimation Mechanism with Local Differential Privacy

inferred← citeshttps://doi.org/10.1109/tkde.2023.3341171openalex-snapshot

EPS2: Privacy Preserving Set-Valued Data Analysis in the Shuffle Model

inferred← citeshttps://doi.org/10.1109/tkde.2025.3593289openalex-snapshot

GeoRecover: Recovery From Poisoning Attacks for LDP-Enabled Spatial Density Aggregation

inferred← citeshttps://doi.org/10.1109/tkde.2026.3652139openalex-snapshot

Fine-Grained Manipulation Attacks to Local Differential Privacy Protocols for Data Streams

inferred← citeshttps://doi.org/10.1109/tkde.2026.3657305openalex-snapshot

Answering Range Queries for Arbitrary Distribution Under Shuffled Differential Privacy

inferred← citeshttps://doi.org/10.1109/tmc.2022.3223578openalex-snapshot

FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps

inferred← citeshttps://doi.org/10.1109/tmc.2023.3343288openalex-snapshot

Federated Learning With Sparsified Model Perturbation: Improving Accuracy Under Client-Level Differential Privacy

inferred← citeshttps://doi.org/10.1109/tmc.2025.3559621openalex-snapshot

Differential Private Data Stream Analytics in the Local and Shuffle Models

inferred← citeshttps://doi.org/10.1109/tnse.2024.3362978openalex-snapshot

Distributed Linear Bandits With Differential Privacy

inferred← citeshttps://doi.org/10.1109/tnse.2026.3665223openalex-snapshot

Beyond LDP-FL: Independent Uplink–Downlink Privacy Protection in Federated Learning

inferred← citeshttps://doi.org/10.1109/tnse.2026.3710233openalex-snapshot

Privacy-Preserving Consensus-Oriented Aggregation for Federated Learning With Heterogeneity

inferred← citeshttps://doi.org/10.1109/tpami.2026.3672569openalex-snapshot

Privacy Preserving Decentralized Learning With Positive-Incentive Noise

inferred← citeshttps://doi.org/10.1109/tpami.2026.3697332openalex-snapshot

Privacy-Preserving Online Federated Learning for Massive Infinite Streams

inferred← citeshttps://doi.org/10.1109/tpds.2022.3167434openalex-snapshot

Differentially Private Byzantine-Robust Federated Learning

inferred← citeshttps://doi.org/10.1109/tpds.2023.3247541openalex-snapshot

Shuffle Differential Private Data Aggregation for Random Population

inferred← citeshttps://doi.org/10.1109/tps-isa58951.2023.00011openalex-snapshot

Ensuring Trust in Genomics Research

inferred← citeshttps://doi.org/10.1109/tps-isa58951.2023.00024openalex-snapshot

Centering Policy and Practice: Research Gaps Around Usable Differential Privacy

inferred← citeshttps://doi.org/10.1109/trustcom63139.2024.00188openalex-snapshot

Real-time Private Data Aggregation over Distributed Spatial-temporal Infinite Streams with Local Differential Privacy

inferred← citeshttps://doi.org/10.1126/sciadv.adh8601openalex-snapshot

PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data

inferred← citeshttps://doi.org/10.1142/s0219691323500200openalex-snapshot

Privacy-preserving federated learning on lattice quantization

inferred← citeshttps://doi.org/10.1145/3320269.3405441openalex-snapshot

POSTER: Data Collection via Local Differential Privacy with Secret Parameters

inferred← citeshttps://doi.org/10.1145/3341301.3359660openalex-snapshot

Honeycrisp

inferred← citeshttps://doi.org/10.1145/3372297.3417261openalex-snapshot

Blinder -- Scalable, Robust Anonymous Committed Broadcast

inferred← citeshttps://doi.org/10.1145/3372297.3417885openalex-snapshot

Secure Single-Server Aggregation with (Poly)Logarithmic Overhead

inferred← citeshttps://doi.org/10.1145/3406325.3450995openalex-snapshot

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

inferred← citeshttps://doi.org/10.1145/3418290openalex-snapshot

DP-cryptography

inferred← citeshttps://doi.org/10.1145/3459637.3482467openalex-snapshot

Random Sampling Plus Fake Data

inferred← citeshttps://doi.org/10.1145/3460120.3484794openalex-snapshot

On the Rényi Differential Privacy of the Shuffle Model

inferred← citeshttps://doi.org/10.1145/3460231.3474262openalex-snapshot

Stronger Privacy for Federated Collaborative Filtering With Implicit Feedback

inferred← citeshttps://doi.org/10.1145/3466752.3480112openalex-snapshot

DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware

inferred← citeshttps://doi.org/10.1145/3488932.3497761openalex-snapshot

Efficient Oblivious Permutation via the Waksman Network

inferred← citeshttps://doi.org/10.1145/3491259openalex-snapshot

BUDS+: Better Privacy with Converger and Noisy Shuffling

inferred← citeshttps://doi.org/10.1145/3508398.3511519openalex-snapshot

Genomic Data Sharing under Dependent Local Differential Privacy

inferred← citeshttps://doi.org/10.1145/3514221.3526162openalex-snapshot

Network Shuffling: Privacy Amplification via Random Walks

inferred← citeshttps://doi.org/10.1145/3514221.3526190openalex-snapshot

LDP-IDS: Local Differential Privacy for Infinite Data Streams

inferred← citeshttps://doi.org/10.1145/3517804.3526226openalex-snapshot

Randomize the Future: Asymptotically Optimal Locally Private Frequency Estimation Protocol for Longitudinal Data

inferred← citeshttps://doi.org/10.1145/3543507.3583512openalex-snapshot

Sanitizing Sentence Embeddings (and Labels) for Local Differential Privacy

inferred← citeshttps://doi.org/10.1145/3548606.3559383openalex-snapshot

Distributed, Private, Sparse Histograms in the Two-Server Model

inferred← citeshttps://doi.org/10.1145/3548606.3560559openalex-snapshot

Selective MPC

inferred← citeshttps://doi.org/10.1145/3548606.3560608openalex-snapshot

Frequency Estimation in the Shuffle Model with Almost a Single Message

inferred← citeshttps://doi.org/10.1145/3548606.3560659openalex-snapshot

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

inferred← citeshttps://doi.org/10.1145/3576915.3616592openalex-snapshot

DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass

inferred← citeshttps://doi.org/10.1145/3576915.3623215openalex-snapshot

Amplification by Shuffling without Shuffling

inferred← citeshttps://doi.org/10.1145/3580305.3599279openalex-snapshot

Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting

inferred← citeshttps://doi.org/10.1145/3605759.3625258openalex-snapshot

A Probabilistic Design for Practical Homomorphic Majority Voting with Intrinsic Differential Privacy

inferred← citeshttps://doi.org/10.1145/3626232.3653279openalex-snapshot

Towards Accurate and Stronger Local Differential Privacy for Federated Learning with Staircase Randomized Response

inferred← citeshttps://doi.org/10.1145/3627106.3627181openalex-snapshot

Differentially Private Resource Allocation

inferred← citeshttps://doi.org/10.1145/3627673.3679911openalex-snapshot

Enhanced Privacy Bound for Shuffle Model with Personalized Privacy

inferred← citeshttps://doi.org/10.1145/3627703.3629559openalex-snapshot

Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy

inferred← citeshttps://doi.org/10.1145/3627703.3629577openalex-snapshot

Snatch: Online Streaming Analytics at the Network Edge

inferred← citeshttps://doi.org/10.1145/3639289openalex-snapshot

Privacy Amplification by Sampling under User-level Differential Privacy

inferred← citeshttps://doi.org/10.1145/3651153openalex-snapshot

Scenario-based Adaptations of Differential Privacy: A Technical Survey

inferred← citeshttps://doi.org/10.1145/3651595openalex-snapshot

Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections

inferred← citeshttps://doi.org/10.1145/3658644.3670391openalex-snapshot

Computationally Secure Aggregation and Private Information Retrieval in the Shuffle Model

inferred← citeshttps://doi.org/10.1145/3658644.3690185openalex-snapshot

S 2 NeRF: Privacy-preserving Training Framework for NeRF

inferred← citeshttps://doi.org/10.1145/3658644.3690200openalex-snapshot

Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy

inferred← citeshttps://doi.org/10.1145/3658644.3690224openalex-snapshot

Samplable Anonymous Aggregation for Private Federated Data Analysis

inferred← citeshttps://doi.org/10.1145/3658644.3690363openalex-snapshot

Metric Differential Privacy at the User-Level via the Earth-Mover's Distance

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