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LDP-Fed

https://doi.org/10.1145/3378679.3394533
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What this work says

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

inferredcites →https://doi.org/10.1002/(sici)1097-024x(199606)26:6<635::aid-spe26>3.0.co;2-popenalex-snapshot
Lua—An Extensible Extension Language
inferredcites →https://doi.org/10.1007/11761679_29openalex-snapshot
Our Data, Ourselves: Privacy Via Distributed Noise Generation
inferredcites →https://doi.org/10.1007/s10994-013-5404-1openalex-snapshot
Bounds on the sample complexity for private learning and private data release
inferredcites →https://doi.org/10.1109/icc.2011.5962863openalex-snapshot
Distributed Data Mining with Differential Privacy
inferredcites →https://doi.org/10.1109/icde.2019.00063openalex-snapshot
Collecting and Analyzing Multidimensional Data with Local Differential Privacy
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2019.00065openalex-snapshot
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2019.2949041openalex-snapshot
Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy
inferredcites →https://doi.org/10.1109/tps-isa48467.2019.00019openalex-snapshot
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability
inferredcites →https://doi.org/10.1109/tsc.2019.2897554openalex-snapshot
Demystifying Membership Inference Attacks in Machine Learning as a Service
inferredcites →https://doi.org/10.1137/090756090openalex-snapshot
What Can We Learn Privately?
inferredcites →https://doi.org/10.1145/2660267.2660348openalex-snapshot
RAPPOR
inferredcites →https://doi.org/10.1145/2810103openalex-snapshot
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3338501.3357370openalex-snapshot
A Hybrid Approach to Privacy-Preserving Federated Learning
inferredcites →https://doi.org/10.4135/9781412952644.n199openalex-snapshot
Health Insurance Portability and Accountability Act
inferredcites →https://doi.org/10.4135/9781452276250.n118openalex-snapshot
Health Insurance Portability and Accountability Act
inferredcites →https://doi.org/10.48550/arxiv.1708.07747openalex-snapshot
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
inferredcites →https://doi.org/10.48550/arxiv.1712.01524openalex-snapshot
Collecting Telemetry Data Privately

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4111927openalex-extracted
Ppnnp: A Privacy-Preserving Neural Network Prediction with Separated Data Providers Using Multi-Client Inner-Product Encryption
inferred← citeshttps://doi.org/10.2139/ssrn.4498327openalex-extracted
inferred← citeshttps://doi.org/10.1002/9781119913924.ch5openalex-snapshot
Deep Federated Learning Based on Knowledge Distillation and Differential Privacy
inferred← citeshttps://doi.org/10.1002/cpe.70473openalex-snapshot
SecureChain: A Blockchain‐Based Secure Model for Sharing Privacy‐Preserved Data Using 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/spy2.374openalex-snapshot
Federated learning with hybrid differential privacy for secure and reliable cross‐IoT platform knowledge sharing
inferred← citeshttps://doi.org/10.1007/978-3-030-66046-8_31openalex-snapshot
Differential Privacy Approach to Solve Gradient Leakage Attack in a Federated Machine Learning Environment
inferred← citeshttps://doi.org/10.1007/978-3-030-93733-1_37openalex-snapshot
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions
inferred← citeshttps://doi.org/10.1007/978-3-031-17140-6_10openalex-snapshot
Local Differential Privacy for Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-37586-6_10openalex-snapshot
Data Distribution Impact on Preserving Privacy in Centralized and Decentralized Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-57567-9_4openalex-snapshot
A Comprehensive Review of Artificial Intelligence and Machine Learning Methods for Modern Healthcare Systems
inferred← citeshttps://doi.org/10.1007/978-3-031-59100-6_2openalex-snapshot
A Survey on Secure Aggregation for Privacy-Preserving Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-65172-4_19openalex-snapshot
Incentivized Federated Learning with Local Differential Privacy Using Permissioned Blockchains
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/10.1007/978-3-031-74643-7_34openalex-snapshot
Re-evaluating the Privacy Benefit of Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-78841-3_7openalex-snapshot
Privacy-Enhancing Technologies for Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-80419-9_11openalex-snapshot
Adaptive Differential Privacy Based Optimization Scheme for Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-86623-4_10openalex-snapshot
Federated Learning with Frequency Estimation for Smart Meter Systems
inferred← citeshttps://doi.org/10.1007/978-3-031-87511-3_6openalex-snapshot
Balancing Privacy and Utility in E-Healthcare Data Analysis: A Comprehensive Review
inferred← citeshttps://doi.org/10.1007/978-3-031-95140-4_10openalex-snapshot
Differentially Private Distributed Frequency Estimation
inferred← citeshttps://doi.org/10.1007/978-3-032-01940-0_5openalex-snapshot
Data Privacy in Enterprise AI
inferred← citeshttps://doi.org/10.1007/978-3-032-06096-9_14openalex-snapshot
Achieving Flexible Local Differential Privacy in Federated Learning via Influence Functions
inferred← citeshttps://doi.org/10.1007/978-3-032-10670-4_16openalex-snapshot
Healthcare Data Privacy Using Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-032-23959-4_6openalex-snapshot
Data-Agnostic MP Techniques
inferred← citeshttps://doi.org/10.1007/978-3-032-23959-4_9openalex-snapshot
Privacy-Utility Trade-Off in Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-032-24804-6_30openalex-snapshot
Effects of Data Heterogeneity and Differential Privacy on Federated Learning
inferred← citeshttps://doi.org/10.1007/978-3-032-38091-3_28openalex-snapshot
FedSwitch: From Standard to Balanced Aggregation via Private Histogram Estimation in Federated Medical Image Classification
inferred← citeshttps://doi.org/10.1007/978-981-19-7083-2_1openalex-snapshot
Introduction
inferred← citeshttps://doi.org/10.1007/978-981-19-8692-5_5openalex-snapshot
Differential Privacy in Federated Learning
inferred← citeshttps://doi.org/10.1007/978-981-95-3055-7_7openalex-snapshot
DRL-SA: Deep Reinforcement Learning-Based Client Selection and Secure Aggregation for Federated Learning
inferred← citeshttps://doi.org/10.1007/978-981-95-4674-9_16openalex-snapshot
Accelerating Simulations of Bitvector-Based LDP Protocols via Binomial Modeling
inferred← citeshttps://doi.org/10.1007/978-981-95-5025-8_5openalex-snapshot
The Projection Onto Algorithm Plane
inferred← citeshttps://doi.org/10.1007/978-981-95-5716-5_19openalex-snapshot
An Efficient Federated Learning Privacy Preservation Method with Differential Privacy Against Model Inversion Attack
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/10.1007/978-981-97-2259-4_19openalex-snapshot
Construct a Secure CNN Against Gradient Inversion Attack
inferred← citeshttps://doi.org/10.1007/978-981-97-5752-7_4openalex-snapshot
Membership Privacy Protection for Federated Learning in Web 3.0
inferred← citeshttps://doi.org/10.1007/978-981-97-7241-4_14openalex-snapshot
PrivRBFN: Building Privacy-Preserving Radial Basis Function Networks Based on Federated Learning
inferred← citeshttps://doi.org/10.1007/978-981-99-4943-4_2openalex-snapshot
Advances in Privacy Preservation Technologies
inferred← citeshttps://doi.org/10.1007/978-981-99-4943-4_4openalex-snapshot
Privacy Computing Techniques
inferred← citeshttps://doi.org/10.1007/978-981-99-8184-7_25openalex-snapshot
Privacy-Preserving Federated Compressed Learning Against Data Reconstruction Attacks Based on Secure Data
inferred← citeshttps://doi.org/10.1007/978-981-99-9247-8_4openalex-snapshot
Current Challenges in Federated Learning: A Review
inferred← citeshttps://doi.org/10.1007/s10207-024-00933-wopenalex-snapshot
Aldp-fl: an adaptive local differential privacy-based federated learning mechanism for IoT
inferred← citeshttps://doi.org/10.1007/s10462-021-10098-wopenalex-snapshot
Federated learning attack surface: taxonomy, cyber defences, challenges, and future directions
inferred← citeshttps://doi.org/10.1007/s10462-023-10563-8openalex-snapshot
A systematic review of federated learning from clients’ perspective: challenges and solutions
inferred← citeshttps://doi.org/10.1007/s10462-024-10766-7openalex-snapshot
A multifaceted survey on privacy preservation of federated learning: progress, challenges, and opportunities
inferred← citeshttps://doi.org/10.1007/s10489-024-06046-0openalex-snapshot
Federated edge learning for medical image augmentation
inferred← citeshttps://doi.org/10.1007/s10586-022-03596-1openalex-snapshot
An empirical analysis of image augmentation against model inversion attack in federated learning
inferred← citeshttps://doi.org/10.1007/s10791-026-10272-0openalex-snapshot
A comprehensive survey on communication optimization and privacy preservation in federated learning
inferred← citeshttps://doi.org/10.1007/s10994-025-06888-wopenalex-snapshot
DP-FedSecure: a secure and efficient federated learning scheme based on adaptive differential privacy
inferred← citeshttps://doi.org/10.1007/s11042-023-16050-0openalex-snapshot
Surveying federated learning approaches through a multi-criteria categorization
inferred← citeshttps://doi.org/10.1007/s11227-025-07593-0openalex-snapshot
AdaS-FLDP: local differentially private federated learning with adaptive sparsification
inferred← citeshttps://doi.org/10.1007/s11227-025-07829-zopenalex-snapshot
Resisting against targeted poisoning attacks in lightweight privacy preserving federated learning
inferred← citeshttps://doi.org/10.1007/s11704-023-2283-xopenalex-snapshot
FedDAA: a robust federated learning framework to protect privacy and defend against adversarial attack
inferred← citeshttps://doi.org/10.1007/s11704-023-3142-5openalex-snapshot
BVDFed: Byzantine-resilient and verifiable aggregation for differentially private federated learning
inferred← citeshttps://doi.org/10.1007/s11704-023-3282-7openalex-snapshot
A survey on federated learning: a perspective from multi-party computation
inferred← citeshttps://doi.org/10.1007/s12083-025-02056-yopenalex-snapshot
EMKPPA: Efficient multi-key privacy-preserving aggregation in federated learning
inferred← citeshttps://doi.org/10.1007/s12083-025-02116-3openalex-snapshot
Privacy-preserving federated learning scheme for distributed smart grid based on multi-key homomorphic encryption
inferred← citeshttps://doi.org/10.1007/s12083-025-02187-2openalex-snapshot
An efficient collusion-resistant and drop-proof federated learning security aggregation scheme based on RLWE
inferred← citeshttps://doi.org/10.1007/s40012-022-00351-0openalex-snapshot
Federated learning to comply with data protection regulations
inferred← citeshttps://doi.org/10.1007/s42979-023-02292-0openalex-snapshot
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond
inferred← citeshttps://doi.org/10.1007/s42979-025-03934-1openalex-snapshot
Advancing Federated Learning: A Comprehensive Solution for Model Aggregation, Heterogeneity, Privacy, and Security
inferred← citeshttps://doi.org/10.1007/s42979-025-04482-4openalex-snapshot
SoK: Towards Privacy-Centric Collaborative Machine Learning—A Classification Framework for Privacy Solutions
inferred← citeshttps://doi.org/10.1016/j.adhoc.2025.103761openalex-snapshot
A hybrid and efficient Federated Learning for privacy preservation in IoT devices
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113800openalex-snapshot
A state alignment-centric approach to federated system identification: The FedAlign framework
inferred← citeshttps://doi.org/10.1016/j.comcom.2026.108468openalex-snapshot
SAFA-MMFL: A human cognition inspired unified framework of task oriented semantic communication for wireless edge devices
inferred← citeshttps://doi.org/10.1016/j.comnet.2021.108671openalex-snapshot
Privacy-preserving blockchain-enabled federated learning for B5G-Driven edge computing
inferred← citeshttps://doi.org/10.1016/j.comnet.2024.110321openalex-snapshot
Towards robust and privacy-preserving federated learning in edge computing
inferred← citeshttps://doi.org/10.1016/j.comnet.2024.110798openalex-snapshot
An Adversarial Machine Learning Based Approach for Privacy Preserving Face Recognition in Distributed Smart City Surveillance
inferred← citeshttps://doi.org/10.1016/j.comnet.2026.112644openalex-snapshot
Privacy-preserving federated deep reinforcement learning with reward shaping and adaptive gradient clipping for vehicular networks
inferred← citeshttps://doi.org/10.1016/j.compag.2021.106648openalex-snapshot
The role of cross-silo federated learning in facilitating data sharing in the agri-food sector
inferred← citeshttps://doi.org/10.1016/j.compag.2025.110048openalex-snapshot
Agricultural data privacy and federated learning: A review of challenges and opportunities
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2025.110070openalex-snapshot
AWE-DPFL: Adaptive weighting and dynamic privacy budget federated learning for heterogeneous data in IoT
inferred← citeshttps://doi.org/10.1016/j.cose.2026.105166openalex-snapshot
Benchmarking post-processing methods in local differential privacy for utility and adversarial robustness
inferred← citeshttps://doi.org/10.1016/j.csi.2022.103678openalex-snapshot
PPNNP: A privacy-preserving neural network prediction with separated data providers using multi-client inner-product encryption
inferred← citeshttps://doi.org/10.1016/j.dcan.2025.07.006openalex-snapshot
DP-Fed6G: An adaptive differential privacy-empowered federated learning framework for 6G networks
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.120266openalex-snapshot
A novel local differential privacy federated learning under multi-privacy regimes
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.126228openalex-snapshot
Privacy-preserving federated learning based on noise addition
inferred← citeshttps://doi.org/10.1016/j.future.2023.06.010openalex-snapshot
Differential privacy in deep learning: Privacy and beyond
inferred← citeshttps://doi.org/10.1016/j.future.2023.07.037openalex-snapshot
Cohort-based kernel principal component analysis with Multi-path Service Routing in Federated Learning
inferred← citeshttps://doi.org/10.1016/j.future.2024.03.041openalex-snapshot
kubeFlower: A privacy-preserving framework for Kubernetes-based federated learning in cloud–edge environments
inferred← citeshttps://doi.org/10.1016/j.future.2025.107848openalex-snapshot
Evaluating privacy loss in differential privacy based federated learning
inferred← citeshttps://doi.org/10.1016/j.future.2026.108518openalex-snapshot
FLSP: A federated learning method with self-adaptive privacy for ensuring high model performance in edge computing
inferred← citeshttps://doi.org/10.1016/j.future.2026.108642openalex-snapshot
BRITE-FL: Blockchain-based reputation and incentive token enhanced federated learning for IoT ecosystems
inferred← citeshttps://doi.org/10.1016/j.inffus.2023.101824openalex-snapshot
Privacy protection in intelligent vehicle networking: A novel federated learning algorithm based on information fusion
inferred← citeshttps://doi.org/10.1016/j.inffus.2024.102420openalex-snapshot
ESVFL: Efficient and secure verifiable federated learning with privacy-preserving
inferred← citeshttps://doi.org/10.1016/j.iot.2024.101344openalex-snapshot
Privacy-preserving estimation of electric vehicle charging behavior: A federated learning approach based on differential privacy
inferred← citeshttps://doi.org/10.1016/j.ipm.2022.103061openalex-snapshot
Federated learning review: Fundamentals, enabling technologies, and future applications
inferred← citeshttps://doi.org/10.1016/j.jare.2024.02.012openalex-snapshot
Semi-supervised Federated Learning for Digital Twin 6G-enabled IIoT: A Bayesian estimated approach
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.01.145openalex-snapshot
An ensemble of random decision trees with local differential privacy in edge computing
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.07.098openalex-snapshot
Federated learning on non-IID data: A survey
inferred← citeshttps://doi.org/10.1016/j.neucom.2024.127345openalex-snapshot
A comprehensive survey and taxonomy on privacy-preserving deep learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.129975openalex-snapshot
Privacy-preserving and Byzantine-robust federated broad learning with chain-loop structure
inferred← citeshttps://doi.org/10.1016/j.simpat.2023.102845openalex-snapshot
PPDF-FedTMI: A Federated Learning-based Transport Mode Inference Model with Privacy-Preserving Data Fusion
inferred← citeshttps://doi.org/10.1038/s41467-023-38794-xopenalex-snapshot
Differentially private knowledge transfer for federated learning
inferred← citeshttps://doi.org/10.1038/s41598-025-01873-8openalex-snapshot
Application of the joint clustering algorithm based on Gaussian kernels and differential privacy in lung cancer identification
inferred← citeshttps://doi.org/10.1038/s41598-025-12575-6openalex-snapshot
ALDP-FL for adaptive local differential privacy in federated learning
inferred← citeshttps://doi.org/10.1049/cmu2.12749openalex-snapshot
Privacy‐preserving data integration scheme in industrial robot system based on fog computing and edge computing
inferred← citeshttps://doi.org/10.1051/itmconf/20257804003openalex-snapshot
Privacy Protection Optimization in Federated Learning
inferred← citeshttps://doi.org/10.1080/14498596.2026.2714779openalex-snapshot
Privacy-preserving spatial keyword query with exclusion keywords and multi-preference support in road networks
inferred← citeshttps://doi.org/10.1088/2058-9565/ad40ccopenalex-snapshot
Privacy-preserving quantum federated learning via gradient hiding
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/access.2022.3214227openalex-snapshot
Accurate and Privacy-Preserving Person Localization Using Federated-Learning and the Camera Surveillance Systems of Public Places
inferred← citeshttps://doi.org/10.1109/access.2023.3234761openalex-snapshot
Enabling All In-Edge Deep Learning: A Literature Review
inferred← citeshttps://doi.org/10.1109/access.2023.3237554openalex-snapshot
Distributed Anomaly Detection in Smart Grids: A Federated Learning-Based Approach
inferred← citeshttps://doi.org/10.1109/access.2023.3263533openalex-snapshot
Visual Object Detection for Privacy-Preserving Federated Learning
inferred← citeshttps://doi.org/10.1109/access.2023.3296143openalex-snapshot
Implementing Privacy-Preserving and Collaborative Industrial Artificial Intelligence
inferred← citeshttps://doi.org/10.1109/access.2023.3304704openalex-snapshot
LAFD: Local-Differentially Private and Asynchronous Federated Learning With Direct Feedback Alignment
inferred← citeshttps://doi.org/10.1109/access.2023.3323020openalex-snapshot
Minimum Gaussian Noise Variance of Federated Learning in the Presence of Mutual Information Based Differential Privacy
inferred← citeshttps://doi.org/10.1109/access.2023.3325396openalex-snapshot
FL-ODP: An Optimized Differential Privacy Enabled Privacy Preserving Federated Learning
inferred← citeshttps://doi.org/10.1109/access.2024.3418016openalex-snapshot
Enhancing Efficiency in Privacy-Preserving Federated Learning for Healthcare: Adaptive Gaussian Clipping With DFT Aggregator
inferred← citeshttps://doi.org/10.1109/access.2024.3433440openalex-snapshot
Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy
inferred← citeshttps://doi.org/10.1109/access.2024.3523909openalex-snapshot
A Survey of Differential Privacy Techniques for Federated Learning
inferred← citeshttps://doi.org/10.1109/access.2025.3605870openalex-snapshot
ClusFed: A Clustering-Based Defense for Secure Federated Learning
inferred← citeshttps://doi.org/10.1109/bigcom57025.2022.00018openalex-snapshot
Federated Learning With Personalized Differential Privacy Combining Client Selection
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386466openalex-snapshot
Differentially Private Federated Learning: Privacy and Utility Analysis of Output Perturbation and DP-SGD
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825512openalex-snapshot
A Defense Mechanism Against LOKI Attacks in Federated Learning for Enhancing Big Data Privacy in Mobile Systems
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825533openalex-snapshot
Toward Efficient Homomorphic Encryption-Based Federated Learning: A Magnitude-Sensitivity Approach
inferred← citeshttps://doi.org/10.1109/candar64496.2024.00023openalex-snapshot
Evaluating Differential Privacy in Federated Continual Learning: A Catastrophic Forgetting-Performance Tradeoff Analysis
inferred← citeshttps://doi.org/10.1109/ccge67142.2026.11581862openalex-snapshot
Securing an Adaptive Federated Learning Framework for Scalable Data to Preserve Privacy in Healthcare
inferred← citeshttps://doi.org/10.1109/ccwc67433.2026.11393858openalex-snapshot
Revisiting Data Anonymization: Limitations and Challenges in the ERA of Large Language Models
inferred← citeshttps://doi.org/10.1109/cic67133.2025.00019openalex-snapshot
Strategic Incentivization for Locally Differentially Private Federated Learning
inferred← citeshttps://doi.org/10.1109/cisat62382.2024.10695226openalex-snapshot
Homomorphic Encryption Based Full Flow Privacy Protection Scheme for Federated Learning
inferred← citeshttps://doi.org/10.1109/cisct62494.2024.11134195openalex-snapshot
Real-Time and Offline Analytics for E-Commerce: A Hybrid Approach Using Apache Kafka, Apache Flink, and Machine Learning
inferred← citeshttps://doi.org/10.1109/codit66093.2025.11321643openalex-snapshot
Adaptive RDP-FL: Enhancing Privacy-Preserving Federated Learning with Robust Differential Privacy Mechanisms
inferred← citeshttps://doi.org/10.1109/cogmi50398.2020.00038openalex-snapshot
Next - Location Prediction Using Federated Learning on a Blockchain
inferred← citeshttps://doi.org/10.1109/comst.2022.3218527openalex-snapshot
Distributed Artificial Intelligence Empowered by End-Edge-Cloud Computing: A Survey
inferred← citeshttps://doi.org/10.1109/comst.2024.3434510openalex-snapshot
Federated Learning for Urban Sensing Systems: A Comprehensive Survey on Attacks, Defences, Incentive Mechanisms, and Applications
inferred← citeshttps://doi.org/10.1109/comst.2024.3486690openalex-snapshot
Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1109/cscwd57460.2023.10152630openalex-snapshot
Dynamic Privacy-Enhanced Federated Learning Algorithm Based on Gradients Perturbation
inferred← citeshttps://doi.org/10.1109/cscwd64889.2025.11033438openalex-snapshot
A Decentralized Federated Learning Framework with Enhanced Privacy and Optimized Fairness
inferred← citeshttps://doi.org/10.1109/cscwd64889.2025.11033540openalex-snapshot
Joint Perturbation and Aggregation for Sparse Gradients in Federated Learning
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11581530openalex-snapshot
Fed-CEP: Federated Causal-Semantic Privacy via Calibrated Input Perturbation
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11581689openalex-snapshot
Enhancing Verifiable Federated Learning with Collusion-Resistant Verification
inferred← citeshttps://doi.org/10.1109/cse66492.2025.00011openalex-snapshot
Age-Aware Incentive Mechanism for Differentially Private Federated Learning Using Stackelberg Game
inferred← citeshttps://doi.org/10.1109/csnt60213.2024.10545944openalex-snapshot
Evolving Data Privacy Norms: Impact and Implications for Energy Internet Pricing Schemes
inferred← citeshttps://doi.org/10.1109/csr64739.2025.11130078openalex-snapshot
LDP3: An Extensible and Multi-Threaded Toolkit for Local Differential Privacy Protocols and Post-Processing Methods
inferred← citeshttps://doi.org/10.1109/dapps61106.2024.00020openalex-snapshot
A Differentially Private Blockchain-Based Approach for Vertical Federated Learning
inferred← citeshttps://doi.org/10.1109/dasc/picom/cbdcom/cy59711.2023.10361468openalex-snapshot
Communication-Efficient Federated Learning with Sparsity and Quantization
inferred← citeshttps://doi.org/10.1109/dsa66321.2025.00070openalex-snapshot
Research on the Reliability of Cloud Edge Collaboration System for AI Applications
inferred← citeshttps://doi.org/10.1109/dsaa61799.2024.10722785openalex-snapshot
AddShare+: Efficient Selective Additive Secret Sharing Approach for Private Federated Learning
inferred← citeshttps://doi.org/10.1109/dsins68311.2025.11330014openalex-snapshot
Privacy-Enhanced Federated Learning Scheme for Location Privacy Preservation
inferred← citeshttps://doi.org/10.1109/dsn-w54100.2022.00018openalex-snapshot
On the impact of non-IID data on the performance and fairness of differentially private federated learning
inferred← citeshttps://doi.org/10.1109/easct59475.2023.10392700openalex-snapshot
MetaFRS- Federated Learning based Cold Start Recommendation System using Meta-Learning
inferred← citeshttps://doi.org/10.1109/eebda53927.2022.9744805openalex-snapshot
A Personalized Privacy-Preserving Scheme for Federated Learning
inferred← citeshttps://doi.org/10.1109/etis64005.2025.10961359openalex-snapshot
Federated Clustering Defense: Mitigating Data Exposure in Collaborative Learning
inferred← citeshttps://doi.org/10.1109/eurosp57164.2023.00020openalex-snapshot
When the Curious Abandon Honesty: Federated Learning Is Not Private
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/fet68771.2026.11601477openalex-snapshot
Federated Edge Intelligence for Privacy-Preserving IoT-Based Smart Banking Systems: Architectures, Security, and Experimental Challenges
inferred← citeshttps://doi.org/10.1109/flta63145.2024.10839934openalex-snapshot
Balancing Privacy and Performance for Private Federated Learning Algorithms
inferred← citeshttps://doi.org/10.1109/fnwf58287.2023.10520497openalex-snapshot
Private and Secure Machine Learning in Wireless Mobile Communication
inferred← citeshttps://doi.org/10.1109/globecom48099.2022.10000632openalex-snapshot
Effects of Quantization on Federated Learning with Local Differential Privacy
inferred← citeshttps://doi.org/10.1109/globecom54140.2023.10437358openalex-snapshot
Joint Knowledge Distillation and Local Differential Privacy for Communication-Efficient Federated Learning in Heterogeneous Systems
inferred← citeshttps://doi.org/10.1109/hpcc-dss-smartcity-dependsys57074.2022.00102openalex-snapshot
Ordinal Data Stream Collection with Condensed Local Differential Privacy
inferred← citeshttps://doi.org/10.1109/icassp39728.2021.9413764openalex-snapshot
Federated Learning with Local Differential Privacy: Trade-Offs Between Privacy, Utility, and Communication
inferred← citeshttps://doi.org/10.1109/icassp55912.2026.11460321openalex-snapshot
Collusion-Resistant and Trusted Authority-Free Verifiable Federated Learning Via a Two-Server Architecture
inferred← citeshttps://doi.org/10.1109/icc42927.2021.9500632openalex-snapshot
COFEL: Communication-Efficient and Optimized Federated Learning with Local Differential Privacy
inferred← citeshttps://doi.org/10.1109/icc59461.2026.11587349openalex-snapshot
Privacy-Preserving Federated Active Learning for Data Completion in Sparse Crowdsensing
inferred← citeshttps://doi.org/10.1109/iccc52777.2021.9580315openalex-snapshot
Communication Reducing Quantization for Federated Learning with Local Differential Privacy Mechanism
inferred← citeshttps://doi.org/10.1109/iccc56324.2022.10065616openalex-snapshot
Minimum Noise Variance in MI-DP Based Federated Learning
inferred← citeshttps://doi.org/10.1109/iccc57788.2023.10233295openalex-snapshot
Privacy-Preserving Model Aggregation for Asynchronous Federated Learning
inferred← citeshttps://doi.org/10.1109/icccn65249.2025.11133897openalex-snapshot
Federated Learning Framework with Personalized Model Compression and Privacy Protection
inferred← citeshttps://doi.org/10.1109/icccs69761.2026.11613274openalex-snapshot
AS-FL: Accumulator and Signature-Based Federated Learning with Weight Aggregation
inferred← citeshttps://doi.org/10.1109/iccect57938.2023.10140219openalex-snapshot
Federated Learning Scheme Based on Gradient Compression and Local Differential Privacy
inferred← citeshttps://doi.org/10.1109/iccect64621.2025.11339734openalex-snapshot
A Survey on Personalized Federated Learning Algorithms: Technical Approaches, Comparative Analysis, and Future Directions
inferred← citeshttps://doi.org/10.1109/icdcs51616.2021.00081openalex-snapshot
Gradient-Leakage Resilient Federated Learning
inferred← citeshttps://doi.org/10.1109/icdcs60910.2024.00070openalex-snapshot
Accelerating and Securing Federated Learning with Stateless In-Network Aggregation at the Edge
inferred← citeshttps://doi.org/10.1109/icde60146.2024.00177openalex-snapshot
Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare
inferred← citeshttps://doi.org/10.1109/icdm65498.2025.00020openalex-snapshot
fair-LDP: Uncertainty-Guided Fairness and Privacy for Federated Healthcare Learning
inferred← citeshttps://doi.org/10.1109/icdm65498.2025.00149openalex-snapshot
Federated Hypergraph Learning with Local Differential Privacy: Toward Privacy-Aware Hypergraph Structure Completion
inferred← citeshttps://doi.org/10.1109/iciibms66230.2025.11316697openalex-snapshot
Publicly verifiable information sharing solution in edge computing scenarios
inferred← citeshttps://doi.org/10.1109/ickii58656.2023.10332562openalex-snapshot
Robust Client Selection Based Secure Collaborative Learning Algorithm for Pneumonia Detection
inferred← citeshttps://doi.org/10.1109/icmla61862.2024.00059openalex-snapshot
SAFARI: Self-regulAted Clustered FederAted Learning in a HeteRogeneous EnvIronment
inferred← citeshttps://doi.org/10.1109/icnp61940.2024.10858511openalex-snapshot
FedSSA: Reducing Overhead of Additive Cryptographic Methods in Federated Learning With Sketch
inferred← citeshttps://doi.org/10.1109/icpads60453.2023.00086openalex-snapshot
Differentially Private Federated Learning via Alternating Direction Method of Multipliers
inferred← citeshttps://doi.org/10.1109/icpads60453.2023.00131openalex-snapshot
FedFC: An Efficient Personalized Federated Learning Method on Non-iid Data
inferred← citeshttps://doi.org/10.1109/icpads67057.2025.11323165openalex-snapshot
Byzantine-Robust and Privacy-Preserving Federated Learning via Two-Stage Two-Party Computation and Compressed Sensing
inferred← citeshttps://doi.org/10.1109/icscsa69367.2026.11708338openalex-snapshot
FedXCrop: Explainable Deep Learning Framework for Multi-Crop Disease Detection
inferred← citeshttps://doi.org/10.1109/icws67624.2025.00056openalex-snapshot
USFCF: Unified State-Space Feedback Control Framework for Robust Privacy-Conscious Federated Learning in Vehicular Service Networks
inferred← citeshttps://doi.org/10.1109/ijcnn54540.2023.10191978openalex-snapshot
PFED-AGG: A Personalized Private Federated Learning Aggregation Algorithm
inferred← citeshttps://doi.org/10.1109/ijcnn60899.2024.10650657openalex-snapshot
FedLRDP: Federated Learning Framework with Local Random Differential Privacy
inferred← citeshttps://doi.org/10.1109/infocom59046.2026.11571699openalex-snapshot
AHE: Adaptive Homomorphic Encryption for Customizable Privacy in Heterogeneous Federated Learning
inferred← citeshttps://doi.org/10.1109/iotais60147.2023.10346071openalex-snapshot
Federated Learning Algorithm Handling Missing Attributes
inferred← citeshttps://doi.org/10.1109/irac63143.2024.10871429openalex-snapshot
An Adaptive Differential Privacy Scheme for Council Mechanism in Decentralized Federated Learning
inferred← citeshttps://doi.org/10.1109/isit45174.2021.9518142openalex-snapshot
Private Multi-Group Aggregation
inferred← citeshttps://doi.org/10.1109/isit54713.2023.10206945openalex-snapshot
Differentially Private Online Federated Learning With Personalization and Fairness
inferred← citeshttps://doi.org/10.1109/isit54713.2023.10206949openalex-snapshot
Differentially Private Secure Multiplication: Hiding Information in the Rubble of Noise
inferred← citeshttps://doi.org/10.1109/isit57864.2024.10619385openalex-snapshot
Achieving the Exactly Optimal Privacy-Utility Trade-Off with Low Communication Cost via Shared Randomness
inferred← citeshttps://doi.org/10.1109/isit57864.2024.10619521openalex-snapshot
Controlled privacy leakage propagation throughout differential private overlapping grouped learning
inferred← citeshttps://doi.org/10.1109/issre66568.2025.00053openalex-snapshot
Enhancing Privacy and Robustness in Federated Learning with Local Data Distribution Invariance and Byzantine-Resilient Aggregation
inferred← citeshttps://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics60724.2023.00047openalex-snapshot
Differentially Private Federated Learning with Heterogeneous Group Privacy
inferred← citeshttps://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics60724.2023.00079openalex-snapshot
Decentralized Reputation-based Leader Election for Privacy-preserving Federated Learning on Internet of Things
inferred← citeshttps://doi.org/10.1109/iucc-cit-dsci-smartcns55181.2021.00019openalex-snapshot
A Secure Federated Learning Mechanism for Data Privacy Protection
inferred← citeshttps://doi.org/10.1109/iwcmc65282.2025.11059634openalex-snapshot
Selective Privacy-Preserving Federated Learning for Large Language Model Fine-Tuning
inferred← citeshttps://doi.org/10.1109/iwqos61813.2024.10682944openalex-snapshot
Fed-CAD: Federated Learning with Correlation-aware Adaptive Local Differential Privacy
inferred← citeshttps://doi.org/10.1109/jetcas.2024.3477348openalex-snapshot
An Overview of Trustworthy AI: Advances in IP Protection, Privacy-preserving Federated Learning, Security Verification, and GAI Safety Alignment
inferred← citeshttps://doi.org/10.1109/jiot.2022.3201231openalex-snapshot
Practical Private Aggregation in Federated Learning Against Inference Attack
inferred← citeshttps://doi.org/10.1109/jiot.2023.3237806openalex-snapshot
Facilitating Early-Stage Backdoor Attacks in Federated Learning With Whole Population Distribution Inference
inferred← citeshttps://doi.org/10.1109/jiot.2023.3238038openalex-snapshot
Accuracy Degrading: Toward Participation-Fair Federated Learning
inferred← citeshttps://doi.org/10.1109/jiot.2023.3264259openalex-snapshot
PPeFL: Privacy-Preserving Edge Federated Learning With Local Differential Privacy
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