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Privacy and Fairness in Federated Learning: On the Perspective of Tradeoff
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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/10.1007/978-3-030-63076-8_2openalex-snapshot
Deep Leakage from Gradients
inferredcites →https://doi.org/10.1007/978-3-030-63076-8_3openalex-snapshot
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
inferredcites →https://doi.org/10.1007/978-3-030-92310-5_80openalex-snapshot
Federated Learning Meets Fairness and Differential Privacy
inferredcites →https://doi.org/10.1007/978-3-319-57959-7openalex-snapshot
The EU General Data Protection Regulation (GDPR)
inferredcites →https://doi.org/10.1007/978-3-642-33486-3_3openalex-snapshot
Fairness-Aware Classifier with Prejudice Remover Regularizer
inferredcites →https://doi.org/10.1007/978-981-10-5421-1_9openalex-snapshot
Privacy-Preserving Deep Learning: Revisited and Enhanced
inferredcites →https://doi.org/10.1007/s10115-011-0463-8openalex-snapshot
Data preprocessing techniques for classification without discrimination
inferredcites →https://doi.org/10.1007/s10506-016-9182-5openalex-snapshot
Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models
inferredcites →https://doi.org/10.1007/s10618-010-0190-xopenalex-snapshot
Three naive Bayes approaches for discrimination-free classification
inferredcites →https://doi.org/10.1016/j.ins.2020.02.037openalex-snapshot
A training-integrity privacy-preserving federated learning scheme with trusted execution environment
inferredcites →https://doi.org/10.1016/j.jnca.2018.05.003openalex-snapshot
Distributed learning of deep neural network over multiple agents
inferredcites →https://doi.org/10.1016/j.neucom.2021.07.098openalex-snapshot
Federated learning on non-IID data: A survey
inferredcites →https://doi.org/10.1016/s0898-1221(96)90463-0openalex-snapshot
Advances in neural information processing systems 7
inferredcites →https://doi.org/10.1016/s1093-3263(98)80012-0openalex-snapshot
The pacific symposium on biocomputing
inferredcites →https://doi.org/10.1073/pnas.1611835114openalex-snapshot
Overcoming catastrophic forgetting in neural networks
inferredcites →https://doi.org/10.1089/big.2016.0047openalex-snapshot
Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments
inferredcites →https://doi.org/10.1089/big.2016.0048openalex-snapshot
Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification
inferredcites →https://doi.org/10.1109/90.879343openalex-snapshot
Fair end-to-end window-based congestion control
inferredcites →https://doi.org/10.1109/bigdata.2018.8622525openalex-snapshot
FairGAN: Fairness-aware Generative Adversarial Networks
inferredcites →https://doi.org/10.1109/bigdata50022.2020.9378043openalex-snapshot
FairFL: A Fair Federated Learning Approach to Reducing Demographic Bias in Privacy-Sensitive Classification Models
inferredcites →https://doi.org/10.1109/csf38047.2016openalex-snapshot
2016 IEEE 29th Computer Security Foundations Symposium (CSF)
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00033openalex-snapshot
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01607openalex-snapshot
See through Gradients: Image Batch Recovery via GradInversion
inferredcites →https://doi.org/10.1109/cvpr52688.2022.00978openalex-snapshot
GradViT: Gradient Inversion of Vision Transformers
inferredcites →https://doi.org/10.1109/cvprw53098.2021.00369openalex-snapshot
Towards Fair Federated Learning with Zero-Shot Data Augmentation
inferredcites →https://doi.org/10.1109/focs.2007.66openalex-snapshot
Mechanism Design via Differential Privacy
inferredcites →https://doi.org/10.1109/globalsip.2013.6736861openalex-snapshot
Stochastic gradient descent with differentially private updates
inferredcites →https://doi.org/10.1109/globecom38437.2019.9014272openalex-snapshot
PEFL: A Privacy-Enhanced Federated Learning Scheme for Big Data Analytics
inferredcites →https://doi.org/10.1109/icassp.2019.8682620openalex-snapshot
Bias Mitigation Post-processing for Individual and Group Fairness
inferredcites →https://doi.org/10.1109/icc.2019.8761315openalex-snapshot
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
inferredcites →https://doi.org/10.1109/icc40277.2020.9148790openalex-snapshot
GAN Enhanced Membership Inference: A Passive Local Attack in Federated Learning
inferredcites →https://doi.org/10.1109/icdmw.2011.83openalex-snapshot
Fairness-aware Learning through Regularization Approach
inferredcites →https://doi.org/10.1109/icip40778.2020.9190968openalex-snapshot
Continual Local Training For Better Initialization Of Federated Models
inferredcites →https://doi.org/10.1109/ieeeconf44664.2019.9049066openalex-snapshot
Federated Learning with Autotuned Communication-Efficient Secure Aggregation
inferredcites →https://doi.org/10.1109/ijcnn48605.2020.9207469openalex-snapshot
Federated learning with hierarchical clustering of local updates to improve training on non-IID data
inferredcites →https://doi.org/10.1109/infcom.2010.5461911openalex-snapshot
An Axiomatic Theory of Fairness in Network Resource Allocation
inferredcites →https://doi.org/10.1109/infocom.2019.8737416openalex-snapshot
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning
inferredcites →https://doi.org/10.1109/infocom41043.2020.9155494openalex-snapshot
Optimizing Federated Learning on Non-IID Data with Reinforcement Learning
inferredcites →https://doi.org/10.1109/jiot.2021.3102030openalex-snapshot
Gain Without Pain: Offsetting DP-Injected Noises Stealthily in Cross-Device Federated Learning
inferredcites →https://doi.org/10.1109/jiot.2021.3112737openalex-snapshot
NOSnoop: An Effective Collaborative Meta-Learning Scheme Against Property Inference Attack
inferredcites →https://doi.org/10.1109/jsac.2020.3000372openalex-snapshot
Analyzing User-Level Privacy Attack Against Federated Learning
inferredcites →https://doi.org/10.1109/jsait.2021.3054610openalex-snapshot
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
inferredcites →https://doi.org/10.1109/mis.2020.2988525openalex-snapshot
A Secure Federated Transfer Learning Framework
inferredcites →https://doi.org/10.1109/sfcs.1982openalex-snapshot
23rd Annual Symposium on Foundations of Computer Science (sfcs 1982)
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/sp37862.2018openalex-snapshot
2018 IEEE Symposium on Security and Privacy (SP)
inferredcites →https://doi.org/10.1109/tdsc.2022.3196646openalex-snapshot
Poisoning-Assisted Property Inference Attack Against Federated Learning
inferredcites →https://doi.org/10.1109/tifs.2019.2911169openalex-snapshot
Privacy-Preserving Deep Learning via Weight Transmission
inferredcites →https://doi.org/10.1109/tifs.2020.2988575openalex-snapshot
Federated Learning With Differential Privacy: Algorithms and Performance Analysis
inferredcites →https://doi.org/10.1109/tifs.2021.3139777openalex-snapshot
Gradient Leakage Attack Resilient Deep Learning
inferredcites →https://doi.org/10.1109/tit.2022.3192506openalex-snapshot
An Efficient Framework for Clustered Federated Learning
inferredcites →https://doi.org/10.1109/tnnls.2020.3015958openalex-snapshot
Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints
inferredcites →https://doi.org/10.1109/tnnls.2021.3129592openalex-snapshot
Balancing Learning Model Privacy, Fairness, and Accuracy With Early Stopping Criteria
inferredcites →https://doi.org/10.1109/tnnls.2022.3160699openalex-snapshot
Towards Personalized Federated Learning
inferredcites →https://doi.org/10.1109/tpds.2020.3009406openalex-snapshot
Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems
inferredcites →https://doi.org/10.1109/tsc.2019.2897554openalex-snapshot
Demystifying Membership Inference Attacks in Machine Learning as a Service
inferredcites →https://doi.org/10.1109/tsmc.1987.4309045openalex-snapshot
Uncertainty in Artificial Intelligence
inferredcites →https://doi.org/10.1109/wacv51458.2022.00366openalex-snapshot
PRECODE - A Generic Model Extension to Prevent Deep Gradient Leakage
inferredcites →https://doi.org/10.1109/worlds450073.2020.9210355openalex-snapshot
Survey of Personalization Techniques for Federated Learning
inferredcites →https://doi.org/10.1137/1.9781611976700.21openalex-snapshot
Fairness-aware Agnostic Federated Learning
inferredcites →https://doi.org/10.1145/2783258.2783311openalex-snapshot
Certifying and Removing Disparate Impact
inferredcites →https://doi.org/10.1145/2810103.2813677openalex-snapshot
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
inferredcites →https://doi.org/10.1145/2810103.2813687openalex-snapshot
Privacy-Preserving Deep Learning
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3133956.3134077openalex-snapshot
Machine Learning Models that Remember Too Much
inferredcites →https://doi.org/10.1145/3194770.3194776openalex-snapshot
Fairness definitions explained
inferredcites →https://doi.org/10.1145/3243734.3243834openalex-snapshot
Property Inference Attacks on Fully Connected Neural Networks using Permutation Invariant Representations
inferredcites →https://doi.org/10.1145/3278721.3278779openalex-snapshot
Mitigating Unwanted Biases with Adversarial Learning
inferredcites →https://doi.org/10.1145/3287560.3287561openalex-snapshot
From Soft Classifiers to Hard Decisions
inferredcites →https://doi.org/10.1145/3308560.3317584openalex-snapshot
Achieving Differential Privacy and Fairness in Logistic Regression
inferredcites →https://doi.org/10.1145/3314183.3323847openalex-snapshot
On the Compatibility of Privacy and Fairness
inferredcites →https://doi.org/10.1145/3351095.3373154openalex-snapshot
Assessing algorithmic fairness with unobserved protected class using data combination
inferredcites →https://doi.org/10.1145/3375627.3375840openalex-snapshot
A Fairness-aware Incentive Scheme for Federated Learning
inferredcites →https://doi.org/10.1145/3447548.3467268openalex-snapshot
Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent
inferredcites →https://doi.org/10.1145/3457607openalex-snapshot
A Survey on Bias and Fairness in Machine Learning
inferredcites →https://doi.org/10.1145/3460427openalex-snapshot
A Comprehensive Survey of Privacy-preserving Federated Learning
inferredcites →https://doi.org/10.1145/3485447.3512233openalex-snapshot
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
inferredcites →https://doi.org/10.1145/3493700.3493750openalex-snapshot
Fair Federated Learning for Heterogeneous Data
inferredcites →https://doi.org/10.1145/3510032openalex-snapshot
GRNN: Generative Regression Neural Network—A Data Leakage Attack for Federated Learning
inferredcites →https://doi.org/10.1177/0049124118782533openalex-snapshot
Fairness in Criminal Justice Risk Assessments: The State of the Art
inferredcites →https://doi.org/10.1177/2053951717743530openalex-snapshot
Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data
inferredcites →https://doi.org/10.1609/aaai.v34i01.5402openalex-snapshot
Differentially Private and Fair Classification via Calibrated Functional Mechanism
inferredcites →https://doi.org/10.1609/aaai.v35i10.17093openalex-snapshot
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning
inferredcites →https://doi.org/10.1609/aaai.v35i11.17193openalex-snapshot
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach
inferredcites →https://doi.org/10.1609/aaai.v35i9.16986openalex-snapshot
Improving Fairness and Privacy in Selection Problems
inferredcites →https://doi.org/10.1609/aaai.v37i6.25911openalex-snapshot
FairFed: Enabling Group Fairness in Federated Learning
inferredcites →https://doi.org/10.1609/aaai.v37i7.25994openalex-snapshot
CertiFair: A Framework for Certified Global Fairness of Neural Networks
inferredcites →https://doi.org/10.1631/fitee.1700813openalex-snapshot
Artificial intelligence and statistics
inferredcites →https://doi.org/10.18653/v1/n18-2003openalex-snapshot
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
inferredcites →https://doi.org/10.18653/v1/n19-3002openalex-snapshot
Identifying and Reducing Gender Bias in Word-Level Language Models
inferredcites →https://doi.org/10.18653/v1/w19-3821openalex-snapshot
Equalizing Gender Bias in Neural Machine Translation with Word Embeddings Techniques
inferredcites →https://doi.org/10.23919/eusipco54536.2021.9616052openalex-snapshot
Federated Learning with Class Imbalance Reduction
inferredcites →https://doi.org/10.24963/ijcai.2021/78openalex-snapshot
Decision Making with Differential Privacy under a Fairness Lens
inferredcites →https://doi.org/10.24963/ijcai.2022/324openalex-snapshot
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
inferredcites →https://doi.org/10.3389/fdata.2019.00013openalex-snapshot
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
inferredcites →https://doi.org/10.3390/app12020734openalex-snapshot
Privacy-Preserving Federated Learning Using Homomorphic Encryption
inferredcites →https://doi.org/10.3390/s21237806openalex-snapshot
Is Homomorphic Encryption-Based Deep Learning Secure Enough?
inferredcites →https://doi.org/10.48550/arxiv.0912.0071openalex-snapshot
Differentially Private Empirical Risk Minimization
inferredcites →https://doi.org/10.48550/arxiv.1607.06520openalex-snapshot
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
inferredcites →https://doi.org/10.48550/arxiv.1610.02413openalex-snapshot
Equality of Opportunity in Supervised Learning
inferredcites →https://doi.org/10.48550/arxiv.1610.05755openalex-snapshot
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
inferredcites →https://doi.org/10.48550/arxiv.1706.02409openalex-snapshot
A Convex Framework for Fair Regression
inferredcites →https://doi.org/10.48550/arxiv.1712.07557openalex-snapshot
Differentially Private Federated Learning: A Client Level Perspective
inferredcites →https://doi.org/10.48550/arxiv.1804.06876openalex-snapshot
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
inferredcites →https://doi.org/10.48550/arxiv.1806.00582openalex-snapshot
Federated Learning with Non-IID Data
inferredcites →https://doi.org/10.48550/arxiv.1806.03287openalex-snapshot
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
inferredcites →https://doi.org/10.48550/arxiv.1807.06689openalex-snapshot
Efficient Deep Learning on Multi-Source Private Data
inferredcites →https://doi.org/10.48550/arxiv.1810.08810openalex-snapshot
The Frontiers of Fairness in Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.1811.03604openalex-snapshot
Federated Learning for Mobile Keyboard Prediction
inferredcites →https://doi.org/10.48550/arxiv.1901.10837openalex-snapshot
Noise-tolerant fair classification
inferredcites →https://doi.org/10.48550/arxiv.1902.08552openalex-snapshot
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment
inferredcites →https://doi.org/10.48550/arxiv.1905.10497openalex-snapshot
Fair Resource Allocation in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.1905.12101openalex-snapshot
Differential Privacy Has Disparate Impact on Model Accuracy
inferredcites →https://doi.org/10.48550/arxiv.1905.12744openalex-snapshot
Fair Decision Making using Privacy-Protected Data
inferredcites →https://doi.org/10.48550/arxiv.1910.03581openalex-snapshot
FedMD: Heterogenous Federated Learning via Model Distillation
inferredcites →https://doi.org/10.48550/arxiv.1910.06044openalex-snapshot
Eavesdrop the Composition Proportion of Training Labels in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.1910.07796openalex-snapshot
Overcoming Forgetting in Federated Learning on Non-IID Data
inferredcites →https://doi.org/10.48550/arxiv.1911.00972openalex-snapshot
Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches
inferredcites →https://doi.org/10.48550/arxiv.2001.02610openalex-snapshot
iDLG: Improved Deep Leakage from Gradients
inferredcites →https://doi.org/10.48550/arxiv.2002.09343openalex-snapshot
Robust Optimization for Fairness with Noisy Protected Groups
inferredcites →https://doi.org/10.48550/arxiv.2002.10619openalex-snapshot
Three Approaches for Personalization with Applications to Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2003.02133openalex-snapshot
Threats to Federated Learning: A Survey
inferredcites →https://doi.org/10.48550/arxiv.2003.13461openalex-snapshot
Adaptive Personalized Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2003.14053openalex-snapshot
Inverting Gradients -- How easy is it to break privacy in federated learning?
inferredcites →https://doi.org/10.48550/arxiv.2004.10397openalex-snapshot
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2008.04975openalex-snapshot
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching
inferredcites →https://doi.org/10.48550/arxiv.2009.06228openalex-snapshot
SAPAG: A Self-Adaptive Privacy Attack From Gradients
inferredcites →https://doi.org/10.48550/arxiv.2010.01243openalex-snapshot
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
inferredcites →https://doi.org/10.48550/arxiv.2010.13356openalex-snapshot
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity Analysis
inferredcites →https://doi.org/10.48550/arxiv.2011.04926openalex-snapshot
Towards a Better Global Loss Landscape of GANs
inferredcites →https://doi.org/10.48550/arxiv.2012.02447openalex-snapshot
Mitigating Bias in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2106.03761openalex-snapshot
FairCal: Fairness Calibration for Face Verification
inferredcites →https://doi.org/10.48550/arxiv.2106.12576openalex-snapshot
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy?
inferredcites →https://doi.org/10.48550/arxiv.2108.04417openalex-snapshot
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
inferredcites →https://doi.org/10.48550/arxiv.2108.08435openalex-snapshot
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2109.00675openalex-snapshot
FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2109.05662openalex-snapshot
Training Fair Models in Federated Learning without Data Privacy Infringement
inferredcites →https://doi.org/10.48550/arxiv.2109.08604openalex-snapshot
Enforcing fairness in private federated learning via the modified method of differential multipliers
inferredcites →https://doi.org/10.48550/arxiv.2110.13057openalex-snapshot
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
inferredcites →https://doi.org/10.48550/arxiv.2111.04706openalex-snapshot
Bayesian Framework for Gradient Leakage
inferredcites →https://doi.org/10.48550/arxiv.2112.00059openalex-snapshot
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2201.07730openalex-snapshot
SCOTCH: An Efficient Secure Computation Framework for Secure Aggregation
inferredcites →https://doi.org/10.48550/arxiv.2206.07737openalex-snapshot
Disparate Impact in Differential Privacy from Gradient Misalignment
inferredcites →https://doi.org/10.48550/arxiv.2206.09888openalex-snapshot
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression
inferredcites →https://doi.org/10.48550/arxiv.2210.02680openalex-snapshot
DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing
inferredcites →https://doi.org/10.48550/arxiv.2210.08781openalex-snapshot
Stochastic Differentially Private and Fair Learning
inferredcites →https://doi.org/10.52202/068431-0590openalex-snapshot
Recovering Private Text in Federated Learning of Language Models
inferredcites →https://doi.org/10.52202/068431-0679openalex-snapshot
PFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning
inferredcites →https://doi.org/10.7544/issn1000-1239.2020.20190455openalex-snapshot
Survey on Privacy-Preserving Machine Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Federated learning system eliminating model drift in distributed edge computing: Theoretical analytics and application on pit engineering state monitoring
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The sound of fairness: An integrative framework for embedding fairness into voice interaction design
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The role of mobile edge computing in advancing federated learning algorithms and techniques: A systematic review of applications, challenges, and future directions
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Personalized differential privacy for high-dimensional data: A random sampling and pruning privacy tree approach
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Hybrid resampling and weighted majority voting for multi-class anomaly detection on imbalanced malware and network traffic data
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.128568openalex-snapshot
Overview of fair federated learning for fairness and privacy preservation
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Artificial intelligence and digital innovations in precision aquaculture: Advancements, applications, and future directions
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Fairness and privacy preserving in federated learning: A survey
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Secure fair aggregation based on category grouping in federated learning
inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103657openalex-snapshot
Distributed machine learning for next-generation communication networks: A survey on privacy, fairness, efficiency, and trade-offs
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Federated learning with context-aware client collaboration: Challenges, advances, and open problems
inferred← citeshttps://doi.org/10.1016/j.infsof.2025.107678openalex-snapshot
Classification and challenges of non-functional requirements in ML-enabled systems: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.ins.2024.120437openalex-snapshot
Supplement data in federated learning with a generator transparent to clients
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Staleness-aware adaptive asynchronous federated learning for secure spatial crowdsourcing
inferred← citeshttps://doi.org/10.1016/j.jisa.2024.103890openalex-snapshot
HierFedPDP:Hierarchical federated learning with personalized differential privacy
inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104255openalex-snapshot
A scalable and semi-supervised approach for Ethereum fraud detection using Graph Neural Networks and K-Nearest Neighbors clustering
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DCMF-BFL: A decentralized consensus multi-factor approach for blockchain-based federated learning
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.111420openalex-snapshot
Fair Federated Learning with Opposite GAN
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Fair Transition Loss: From label noise robustness to bias mitigation
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.113392openalex-snapshot
F3 : Fair Federated Learning Framework with adaptive regularization
inferred← citeshttps://doi.org/10.1016/j.neunet.2025.107874openalex-snapshot
Linkage on security, privacy and fairness in federated learning: New balances and new perspectives
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Federated learning energy saving through client selection
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A combined approach of evolutionary game and system dynamics for user privacy protection in human intelligence interaction
inferred← citeshttps://doi.org/10.1080/08839514.2026.2663618openalex-snapshot
Intelligent Aggregation Federation: A Learning-Based Metasystem for Secure and Robust Federated Learning in Finance
inferred← citeshttps://doi.org/10.1088/2631-8695/ae39a5openalex-snapshot
A bearing fault diagnosis method based on an incremental broad federated learning system
inferred← citeshttps://doi.org/10.1093/bib/bbae356openalex-snapshot
Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision
inferred← citeshttps://doi.org/10.1109/access.2024.3413069openalex-snapshot
A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward
inferred← citeshttps://doi.org/10.1109/access.2026.3718281openalex-snapshot
Fairness-Aware Federated Learning Framework for ICU Mortality Prediction
inferred← citeshttps://doi.org/10.1109/auteee67053.2025.11322388openalex-snapshot
Enabling Role of Post-Quantum Secure Multi-Party Private Intersection Protocol in Federated Learning
inferred← citeshttps://doi.org/10.1109/ccgridw69005.2026.00048openalex-snapshot
Enhancing Fairness in Federated Learning Using Client Clustering and Personalized Models
inferred← citeshttps://doi.org/10.1109/cvpr52733.2024.01148openalex-snapshot
Fair Federated Learning Under Domain Skew with Local Consistency and Domain Diversity
inferred← citeshttps://doi.org/10.1109/eeite61750.2024.10654397openalex-snapshot
The Future of Privacy: A Review on AI's Role in Shaping Data Security
inferred← citeshttps://doi.org/10.1109/eucnc/6gsummit60053.2024.10597130openalex-snapshot
Multi-Layer Distributed Learning for Intelligent Transportation Systems in 6G Aerial-Ground Integrated Networks
inferred← citeshttps://doi.org/10.1109/flics70075.2026.11621940openalex-snapshot
Robust Server Defense Against Unreliable Clients in One-Shot Fair Collaborative Machine Learning
inferred← citeshttps://doi.org/10.1109/icadcs70036.2026.11582991openalex-snapshot
Civic Tech an AI Powered Community Reporting Platform for Urban Infrastructure Management
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/icicr65456.2025.00126openalex-snapshot
Research on the Application of Computer Intelligent Proofreading System in English Phrase Translation
inferred← citeshttps://doi.org/10.1109/icsseecc69062.2026.11722174openalex-snapshot
Bias Breaker: A Privacy-Preserving and Generative Framework for Fairness Evaluation
inferred← citeshttps://doi.org/10.1109/infocomwkshps65812.2025.11152801openalex-snapshot
Privacy-Preserving Data Auditing with Efficient Corrupted Data Locating for Cloud Computing
inferred← citeshttps://doi.org/10.1109/ipdpsw66978.2025.00087openalex-snapshot
Parallel Processing for Distributed Machine Learning: A Taxonomy of Techniques and Associated Security Risks
inferred← citeshttps://doi.org/10.1109/isc266238.2025.11293299openalex-snapshot
Fairchoice: Balancing Performance and Group Fairness in Federated Learning with Non-IID Data
inferred← citeshttps://doi.org/10.1109/jcice71302.2026.11682286openalex-snapshot
Entropy-Regularized Scheduling and Physics-Aware Aggregation for Fair Federated Learning in Internet of Vehicles
inferred← citeshttps://doi.org/10.1109/jiot.2024.3460349openalex-snapshot
RATE: Game-Theoretic Design of Sustainable Incentive Mechanism for Federated Learning
inferred← citeshttps://doi.org/10.1109/jiot.2025.3598127openalex-snapshot
GPFL: A Gradient Projection-Based Client Selection Framework for Efficient Federated Learning
inferred← citeshttps://doi.org/10.1109/jiot.2026.3717620openalex-snapshot
A Fairness-Aware Query-Adaptive Differential Privacy Mechanism for Collusion-Resistant Flexibility Data Sharing in IoT-Enabled Virtual Power Plants
inferred← citeshttps://doi.org/10.1109/mnet.2024.3522477openalex-snapshot
Optimizing Model-Driven Federated Learning for Rational and Data-Efficient in Social Mobile Network
inferred← citeshttps://doi.org/10.1109/ojcoms.2024.3435389openalex-snapshot
FedCPD: A Federated Learning Algorithm for Processing and Securing Distributed Heterogeneous Data in the Metaverse
inferred← citeshttps://doi.org/10.1109/ojcoms.2024.3438264openalex-snapshot
Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects
inferred← citeshttps://doi.org/10.1109/scecs65243.2025.11065582openalex-snapshot
Personalized Differential Privacy Client Selection: A Loss and Privacy Budget based Approach
inferred← citeshttps://doi.org/10.1109/smc58881.2025.11343527openalex-snapshot
PFL-SA: Personalized federated learning with switchable aggregation strategy
inferred← citeshttps://doi.org/10.1109/sp54263.2024.00243openalex-snapshot
SoK: Unintended Interactions among Machine Learning Defenses and Risks
inferred← citeshttps://doi.org/10.1109/tc.2025.3642408openalex-snapshot
FedInf: An Efficient and Secure Inference With Federated Participants
inferred← citeshttps://doi.org/10.1109/tce.2025.3571956openalex-snapshot
Fuzzified Federated Multi-Task Unlearning for Efficient and Privacy-Preserving Swarm Consumer Electronics Systems
inferred← citeshttps://doi.org/10.1109/tce.2026.3656232openalex-snapshot
Privacy-Preserving Multi-Party Transaction Auditing for Social Financial Technology
inferred← citeshttps://doi.org/10.1109/tcss.2025.3603719openalex-snapshot
FedSCOPE: A Comprehensive Evaluation Framework for Federated Learning in Human-Centered Social Computing
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3601844openalex-snapshot
Untargeted Poisoning Membership Inference With Sample Selection and Enhancement
inferred← citeshttps://doi.org/10.1109/tifs.2024.3416042openalex-snapshot
Secure Model Aggregation Against Poisoning Attacks for Cross-Silo Federated Learning With Robustness and Fairness
inferred← citeshttps://doi.org/10.1109/tifs.2026.3671126openalex-snapshot
A Fine-Tuning Data Recovery Attack on Generative Language Models via Backdooring
inferred← citeshttps://doi.org/10.1109/tkde.2026.3719932openalex-snapshot
Fairness in Augmented Graph Learning: A Survey
inferred← citeshttps://doi.org/10.1109/tmc.2025.3529487openalex-snapshot
SnapCFL: A Pre-Clustering-Based Clustered Federated Learning Framework for Data and System Heterogeneities
inferred← citeshttps://doi.org/10.1109/tmc.2025.3613253openalex-snapshot
Towards Generalization Fairness in Federated Learning
inferred← citeshttps://doi.org/10.1109/tnse.2026.3690657openalex-snapshot
Hierarchical Negotiation-Debate Framework for Privacy-Preserving Quality Enhancement in Edge Intelligence Networks
inferred← citeshttps://doi.org/10.1109/ton.2025.3644644openalex-snapshot
Mitigating Server-Side Communication Bottlenecks in Distributed Learning With Round-Robin Participant Coordination
inferred← citeshttps://doi.org/10.1109/tpami.2025.3548729openalex-snapshot
Graph Foundation Models: Concepts, Opportunities and Challenges
inferred← citeshttps://doi.org/10.1109/tsc.2025.3562359openalex-snapshot
Robust Federated Learning for Privacy Preservation and Efficiency in Edge Computing
inferred← citeshttps://doi.org/10.1145/3656165openalex-snapshot
Horizontal Federated Recommender System: A Survey
inferred← citeshttps://doi.org/10.1145/3704633openalex-snapshot
Membership Inference Attacks and Defenses in Federated Learning: A Survey
inferred← citeshttps://doi.org/10.1145/3711618.3711641openalex-snapshot
Decentralized Federated Learning with Local Differential Privacy and Comprehensive Neighbor Selection
inferred← citeshttps://doi.org/10.1145/3720480openalex-snapshot
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification
inferred← citeshttps://doi.org/10.1145/3720539openalex-snapshot
Vertical Federated Learning for Effectiveness, Security, Applicability: A Survey
inferred← citeshttps://doi.org/10.1145/3724113openalex-snapshot
The Federation Strikes Back: A Survey of Federated Learning Privacy Attacks, Defenses, Applications, and Policy Landscape
inferred← citeshttps://doi.org/10.1145/3735125openalex-snapshot
Bias in Federated Learning: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1145/3810232openalex-snapshot
CurvFed: Curvature-Aligned Federated Learning for Fairness without Demographics
inferred← citeshttps://doi.org/10.1287/ijoc.2024.0554openalex-snapshot
Privacy Protection and Statistical Efficiency Trade-Off for Federated Learning
inferred← citeshttps://doi.org/10.18280/isi.290605openalex-snapshot
Bias in Federated Learning: Factors, Effects, Mitigations, and Open Issues
inferred← citeshttps://doi.org/10.2139/ssrn.6278648openalex-snapshot
MOSAIC: Modeling Original Statistics via Aligned Image Composition for Data-Free Distillation
inferred← citeshttps://doi.org/10.2139/ssrn.6387101openalex-snapshot
TailorFed: Group-Fairness-Aware Personalized Federated Learning
inferred← citeshttps://doi.org/10.23919/wiopt71098.2026.11568230openalex-snapshot
When the Server Steps In: Calibrated Updates for Fair Federated Learning
inferred← citeshttps://doi.org/10.3103/s0147688225700546openalex-snapshot
Ethical Aspects of the Use of Artificial Intelligence Technologies: State of the Art and Prospects for Regulation
inferred← citeshttps://doi.org/10.3390/bs15010027openalex-snapshot
Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis
inferred← citeshttps://doi.org/10.3390/network5030041openalex-snapshot
Unified Distributed Machine Learning for 6G Intelligent Transportation Systems: A Hierarchical Approach for Terrestrial and Non-Terrestrial Networks
inferred← citeshttps://doi.org/10.51847/y0yunxq0ggopenalex-snapshot
Federated Learning for Cross-Institutional Phytochemical Discovery: Collaborative Model Development Without Centralized Sensitive Data Sharing
inferred← citeshttps://doi.org/10.5753/eniac.2024.245212openalex-snapshot
Privacy-Preserving k-NN Graphs with Autoencoder-Based Representations for Sensitive Features
inferred← citeshttps://doi.org/10.5753/jisa.2024.4006openalex-snapshot
The Impact of Federated Learning on Urban Computing
inferred← citeshttps://doi.org/10.7717/peerj-cs.3235openalex-snapshot
Chatbots integrated in the metaverse: a conceptual model based on interaction ritual chain theory
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