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Membership Inference Attacks and Defenses in Federated Learning: A Survey
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Calibrating Noise to Sensitivity in Private Data Analysis
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Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks
inferredcites →https://doi.org/10.1007/978-3-031-01585-4_5openalex-snapshot
Vertical Federated Learning
inferredcites →https://doi.org/10.1007/978-3-031-18523-6_14openalex-snapshot
Towards Sparsified Federated Neuroimaging Models via Weight Pruning
inferredcites →https://doi.org/10.1007/978-3-031-25201-3_28openalex-snapshot
FD-Leaks: Membership Inference Attacks Against Federated Distillation Learning
inferredcites →https://doi.org/10.1007/978-3-031-70365-2_11openalex-snapshot
Secure Aggregation Is Not Private Against Membership Inference Attacks
inferredcites →https://doi.org/10.1007/978-981-97-5562-2_14openalex-snapshot
LDP-Purifier: Defending against Poisoning Attacks in Local Differential Privacy
inferredcites →https://doi.org/10.1007/s41666-020-00082-4openalex-snapshot
Federated Learning for Healthcare Informatics
inferredcites →https://doi.org/10.1016/j.cose.2021.102378openalex-snapshot
Digestive neural networks: A novel defense strategy against inference attacks in federated learning
inferredcites →https://doi.org/10.1016/j.ins.2023.02.025openalex-snapshot
Model poisoning attack in differential privacy-based federated learning
inferredcites →https://doi.org/10.1016/j.jisa.2022.103201openalex-snapshot
CS-MIA: Membership inference attack based on prediction confidence series in federated learning
inferredcites →https://doi.org/10.1016/j.knosys.2021.106775openalex-snapshot
A survey on federated learning
inferredcites →https://doi.org/10.1016/j.neucom.2021.04.082openalex-snapshot
Resisting membership inference attacks through knowledge distillation
inferredcites →https://doi.org/10.1016/j.psychres.2021.114135openalex-snapshot
Detecting formal thought disorder by deep contextualized word representations
inferredcites →https://doi.org/10.1080/01621459.2019.1700130openalex-snapshot
Privacy-Preserving Parametric Inference: A Case for Robust Statistics
inferredcites →https://doi.org/10.1109/access.2021.3075203openalex-snapshot
Vulnerabilities in Federated Learning
inferredcites →https://doi.org/10.1109/bigdata47090.2019.9005992openalex-snapshot
Privacy-preserving Heterogeneous Federated Transfer Learning
inferredcites →https://doi.org/10.1109/bigdata47090.2019.9006280openalex-snapshot
Secure and Efficient Federated Transfer Learning
inferredcites →https://doi.org/10.1109/comst.2021.3075439openalex-snapshot
Federated Learning for Internet of Things: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/comst.2021.3090430openalex-snapshot
Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges
inferredcites →https://doi.org/10.1109/csf.2018.00027openalex-snapshot
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
inferredcites →https://doi.org/10.1109/csf57540.2023.00013openalex-snapshot
Investigating Membership Inference Attacks under Data Dependencies
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00780openalex-snapshot
On the Difficulty of Membership Inference Attacks
inferredcites →https://doi.org/10.1109/cvpr52734.2025.01922openalex-snapshot
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
inferredcites →https://doi.org/10.1109/dsn58367.2023.00037openalex-snapshot
Fortifying Federated Learning against Membership Inference Attacks via Client-level Input Perturbation
inferredcites →https://doi.org/10.1109/globecom48099.2022.10001614openalex-snapshot
A New Implementation of Federated Learning for Privacy and Security Enhancement
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/icccn49398.2020.9209744openalex-snapshot
Beyond Model-Level Membership Privacy Leakage: an Adversarial Approach in Federated Learning
inferredcites →https://doi.org/10.1109/icccs52626.2021.9449214openalex-snapshot
A Method to Improve the Privacy and Security for Federated Learning
inferredcites →https://doi.org/10.1109/iccv48922.2021.01455openalex-snapshot
Membership Inference Attacks are Easier on Difficult Problems
inferredcites →https://doi.org/10.1109/icdm.2019.00056openalex-snapshot
Performing Co-membership Attacks Against Deep Generative Models
inferredcites →https://doi.org/10.1109/icdm51629.2021.00129openalex-snapshot
Source Inference Attacks in Federated Learning
inferredcites →https://doi.org/10.1109/icirca48905.2020.9183133openalex-snapshot
Privacy Preserving Deep Learning using Secure Multiparty Computation
inferredcites →https://doi.org/10.1109/icnc59896.2024.10556313openalex-snapshot
MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated Learning
inferredcites →https://doi.org/10.1109/icpads47876.2019.00042openalex-snapshot
Understanding Distributed Poisoning Attack in Federated Learning
inferredcites →https://doi.org/10.1109/infocom.2018.8486352openalex-snapshot
InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy
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/jiot.2020.3017377openalex-snapshot
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices
inferredcites →https://doi.org/10.1109/jiot.2020.3028110openalex-snapshot
Exploiting Unintended Property Leakage in Blockchain-Assisted Federated Learning for Intelligent Edge Computing
inferredcites →https://doi.org/10.1109/jsac.2020.3000373openalex-snapshot
Robust Coreset Construction for Distributed Machine Learning
inferredcites →https://doi.org/10.1109/mis.2020.2988525openalex-snapshot
A Secure Federated Transfer Learning Framework
inferredcites →https://doi.org/10.1109/mis.2020.3010335openalex-snapshot
Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning?
inferredcites →https://doi.org/10.1109/msec.2020.3039941openalex-snapshot
A Taxonomy of Attacks on Federated Learning
inferredcites →https://doi.org/10.1109/msn53354.2021.00036openalex-snapshot
Defending against Membership Inference Attacks in Federated learning via Adversarial Example
inferredcites →https://doi.org/10.1109/nana53684.2021.00062openalex-snapshot
A survey on security and privacy threats to federated learning
inferredcites →https://doi.org/10.1109/nca51143.2020.9306745openalex-snapshot
Federated vs. Centralized Machine Learning under Privacy-elastic Users: A Comparative Analysis
inferredcites →https://doi.org/10.1109/sp.2017.12openalex-snapshot
SecureML: A System for Scalable Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2019.00029openalex-snapshot
Exploiting Unintended Feature Leakage in Collaborative Learning
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/sp40001.2021.00069openalex-snapshot
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning
inferredcites →https://doi.org/10.1109/sp46214.2022.9833649openalex-snapshot
Membership Inference Attacks From First Principles
inferredcites →https://doi.org/10.1109/sp46215.2023.10179401openalex-snapshot
3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning
inferredcites →https://doi.org/10.1109/spw53761.2021.00017openalex-snapshot
SAFELearn: Secure Aggregation for private FEderated Learning
inferredcites →https://doi.org/10.1109/tdsc.2021.3128679openalex-snapshot
Secure Aggregation is Insecure: Category Inference Attack on Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2022.3222880openalex-snapshot
Membership Inference Attacks Against Deep Learning Models via Logits Distribution
inferredcites →https://doi.org/10.1109/tdsc.2023.3326230openalex-snapshot
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning
inferredcites →https://doi.org/10.1109/tifs.2017.2787987openalex-snapshot
Privacy-Preserving Deep Learning via Additively Homomorphic Encryption
inferredcites →https://doi.org/10.1109/tifs.2023.3303718openalex-snapshot
TEAR: Exploring Temporal Evolution of Adversarial Robustness for Membership Inference Attacks Against Federated Learning
inferredcites →https://doi.org/10.1109/tkde.2021.3124599openalex-snapshot
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
inferredcites →https://doi.org/10.1109/tnnls.2022.3160699openalex-snapshot
Towards Personalized Federated Learning
inferredcites →https://doi.org/10.1109/tnnls.2022.3216981openalex-snapshot
Privacy and Robustness in Federated Learning: Attacks and Defenses
inferredcites →https://doi.org/10.1109/tsc.2019.2897554openalex-snapshot
Demystifying Membership Inference Attacks in Machine Learning as a Service
inferredcites →https://doi.org/10.1145/2810103.2813677openalex-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/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3133956.3133982openalex-snapshot
Practical Secure Aggregation for Privacy-Preserving Machine Learning
inferredcites →https://doi.org/10.1145/3319535.3354211openalex-snapshot
Privacy Risks of Securing Machine Learning Models against Adversarial Examples
inferredcites →https://doi.org/10.1145/3338501.3357370openalex-snapshot
A Hybrid Approach to Privacy-Preserving Federated Learning
inferredcites →https://doi.org/10.1145/3394486.3403298openalex-snapshot
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
inferredcites →https://doi.org/10.1145/3460120.3484575openalex-snapshot
Membership Leakage in Label-Only Exposures
inferredcites →https://doi.org/10.1145/3460120.3484749openalex-snapshot
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive 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/10.1145/3501296openalex-snapshot
Federated Learning for Smart Healthcare: A Survey
inferredcites →https://doi.org/10.1145/3543507.3583359openalex-snapshot
Interaction-level Membership Inference Attack Against Federated Recommender Systems
inferredcites →https://doi.org/10.1145/3543507.3583542openalex-snapshot
AgrEvader: Poisoning Membership Inference against Byzantine-robust Federated Learning
inferredcites →https://doi.org/10.1145/3548606.3560684openalex-snapshot
Membership Inference Attacks by Exploiting Loss Trajectory
inferredcites →https://doi.org/10.1145/3579856.3590334openalex-snapshot
LoDen: Making Every Client in Federated Learning a Defender Against the Poisoning Membership Inference Attacks
inferredcites →https://doi.org/10.1145/3591197.3593638openalex-snapshot
Membership Inference Vulnerabilities in Peer-to-Peer Federated Learning
inferredcites →https://doi.org/10.1145/3606017openalex-snapshot
Privacy and Fairness in Federated Learning: On the Perspective of Tradeoff
inferredcites →https://doi.org/10.1145/3607199.3607204openalex-snapshot
Efficient Membership Inference Attacks against Federated Learning via Bias Differences
inferredcites →https://doi.org/10.1145/3620667openalex-snapshot
Defenses to Membership Inference Attacks: A Survey
inferredcites →https://doi.org/10.1155/2021/5534270openalex-snapshot
User‐Level Membership Inference for Federated Learning in Wireless Network Environment
inferredcites →https://doi.org/10.1155/2022/1615476openalex-snapshot
Membership Inference Defense in Distributed Federated Learning Based on Gradient Differential Privacy and Trust Domain Division Mechanisms
inferredcites →https://doi.org/10.1371/journal.pgen.1000167openalex-snapshot
Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
inferredcites →https://doi.org/10.14722/ndss.2018.23183openalex-snapshot
Knock Knock, Who's There? Membership Inference on Aggregate Location Data
inferredcites →https://doi.org/10.14722/ndss.2019.23119openalex-snapshot
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
inferredcites →https://doi.org/10.14722/ndss.2021.24434openalex-snapshot
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping
inferredcites →https://doi.org/10.14722/ndss.2022.23054openalex-snapshot
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
inferredcites →https://doi.org/10.14778/3484224.3484231openalex-snapshot
Quantifying identifiability to choose and audit ϵ in differentially private deep learning
inferredcites →https://doi.org/10.1561/2200000083openalex-snapshot
Advances and Open Problems in Federated Learning
inferredcites →https://doi.org/10.1609/aaai.v34i04.5793openalex-snapshot
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning
inferredcites →https://doi.org/10.1609/aaai.v34i04.5895openalex-snapshot
Practical Federated Gradient Boosting Decision Trees
inferredcites →https://doi.org/10.1609/aaai.v35i9.16960openalex-snapshot
Personalized Cross-Silo Federated Learning on Non-IID Data
inferredcites →https://doi.org/10.1631/fitee.1700813openalex-snapshot
Artificial intelligence and statistics
inferredcites →https://doi.org/10.18653/v1/d17-1045openalex-snapshot
Sparse Communication for Distributed Gradient Descent
inferredcites →https://doi.org/10.2478/popets-2021-0031openalex-snapshot
Revisiting Membership Inference Under Realistic Assumptions
inferredcites →https://doi.org/10.3934/mfc.2018015openalex-snapshot
Cryptographic algorithms for privacy-preserving online applications
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
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.1805.07337openalex-snapshot
Reconstruction of training samples from loss functions
inferredcites →https://doi.org/10.48550/arxiv.1810.05291openalex-snapshot
signSGD with Majority Vote is Communication Efficient And Fault Tolerant
inferredcites →https://doi.org/10.48550/arxiv.1811.03604openalex-snapshot
Federated Learning for Mobile Keyboard Prediction
inferredcites →https://doi.org/10.48550/arxiv.1912.11279openalex-snapshot
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer
inferredcites →https://doi.org/10.48550/arxiv.2001.02610openalex-snapshot
iDLG: Improved Deep Leakage from Gradients
inferredcites →https://doi.org/10.48550/arxiv.2003.02133openalex-snapshot
Threats to Federated Learning: A Survey
inferredcites →https://doi.org/10.48550/arxiv.2010.12229openalex-snapshot
Throughput-Optimal Topology Design for Cross-Silo Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2103.01116openalex-snapshot
Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles
inferredcites →https://doi.org/10.48550/arxiv.2206.03317openalex-snapshot
Subject Membership Inference Attacks in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.2206.03617openalex-snapshot
Subject Granular Differential Privacy in Federated Learning
inferredcites →https://doi.org/10.5555/2567709.2502603openalex-snapshot
Differential privacy for functions and functional data
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Federated learning framework for predicting multi-drug resistant tuberculosis across regional databases
inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104251openalex-snapshot
Decentralized Federated Learning with Multimodal Prototypes for Heterogeneous Data
inferred← citeshttps://doi.org/10.1016/j.ins.2026.124297openalex-snapshot
CIPHER-fed: An inference-resistant federated learning framework via structural gradient obfuscation
inferred← citeshttps://doi.org/10.1016/j.iot.2026.101973openalex-snapshot
Threat landscape of Edge-AI-assisted connected autonomous vehicles (CAV)
inferred← citeshttps://doi.org/10.1016/j.ipm.2025.104424openalex-snapshot
Knowledge precedence networks: Mining progression patterns of scientific discoveries beyond prerequisites
inferred← citeshttps://doi.org/10.1016/j.iswa.2025.200529openalex-snapshot
Disruptive attacks on artificial neural networks: A systematic review of attack techniques, detection methods, and protection strategies
inferred← citeshttps://doi.org/10.1016/j.jisa.2025.104302openalex-snapshot
Enhancing black-box membership inference attacks in federated learning
inferred← citeshttps://doi.org/10.1016/j.jisa.2026.104564openalex-snapshot
Secure and efficient federated learning using attribute-based homomorphic encryption
inferred← citeshttps://doi.org/10.1016/j.jisa.2026.104608openalex-snapshot
Security and privacy-preserving mechanisms in collaborative machine learning: A systematic review with novel taxonomy
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.116784openalex-snapshot
Data-centric deep learning for defect detection in fiber composite materials: A review of algorithms, challenges, and emerging trends
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.116853openalex-snapshot
FDHNet: Frequency-aware decomposition with hypergraph modeling network for real-time surface defect segmentation
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.117105openalex-snapshot
EMR-GAN: Process improvement, privacy preserving data generation, and prediction enhancement based on GAN
inferred← citeshttps://doi.org/10.1016/j.matchar.2026.116560openalex-snapshot
Direct 3D segmentation and classification of defects in metal additive manufacturing using multi-scale deep learning on XCT data
inferred← citeshttps://doi.org/10.1016/j.sasc.2026.200605openalex-snapshot
Noise-coordinated federated reinforcement learning for campus edge Internet of Things
inferred← citeshttps://doi.org/10.1016/j.sysarc.2025.103671openalex-snapshot
Thwarting gradient inversion in federated learning via generative shadow mapping defense
inferred← citeshttps://doi.org/10.1016/j.sysarc.2026.103903openalex-snapshot
Fisher-guided selective homomorphic encryption for privacy-efficient federated fine-tuning
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/10.1088/1742-6596/3216/1/012024openalex-snapshot
Electromagnetic non-destructive testing for defect detection in copper plate processing using intelligent techniques
inferred← citeshttps://doi.org/10.1108/atsip-01-2026-0004openalex-snapshot
FLRSP: privacy-preserving federated learning using randomly selected model parameters
inferred← citeshttps://doi.org/10.1109/access.2025.3587345openalex-snapshot
Blockchain-Enabled Federated Learning in Healthcare: Survey and State-of-the-Art
inferred← citeshttps://doi.org/10.1109/apsec66846.2025.00076openalex-snapshot
Exposing and Defending Membership Leakage in Vulnerability Prediction Models
inferred← citeshttps://doi.org/10.1109/cbd69312.2025.00053openalex-snapshot
SHDual-Mask: a Dual Masking Framework for Privacy-Preserving Federated Learning in IoT
inferred← citeshttps://doi.org/10.1109/ccwc67433.2026.11393736openalex-snapshot
A Privacy-Preserving Data Pipeline Architecture for Federated and Generative AI Collaboration
inferred← citeshttps://doi.org/10.1109/comst.2026.3659793openalex-snapshot
6G AI Security: From Fundamentals to Offensive and Defensive Landscape in 6G
inferred← citeshttps://doi.org/10.1109/cscwd68734.2026.11581716openalex-snapshot
Fed-SENSE: Federated State-Aware Null-Space Ensemble for Evasive Learning
inferred← citeshttps://doi.org/10.1109/csr64739.2025.11130099openalex-snapshot
Machine Learning Model Complexity as a Mitigation Strategy Against Industrial Espionage through Membership Inference Attacks
inferred← citeshttps://doi.org/10.1109/cvprf71909.2026.00771openalex-snapshot
PLR-Gate: Real-Time Gradient Privacy Assessment and Gated Transmission for Secure Federated Learning
inferred← citeshttps://doi.org/10.1109/ets69887.2026.11591888openalex-snapshot
A CIM-based Gaussian Random Number Generator for Edge Devices as Security Primitive
inferred← citeshttps://doi.org/10.1109/fllm67465.2025.11391117openalex-snapshot
Privacy-Preserving Learning and Inference in Foundation Models for Secure AI Applications
inferred← citeshttps://doi.org/10.1109/globecom59602.2025.11432262openalex-snapshot
Effective Dual-Layer Poison Attacks Detection in Privacy-preserving Federated Learning
inferred← citeshttps://doi.org/10.1109/iccv51701.2025.00293openalex-snapshot
Reminiscence Attack on Residuals: Exploiting Approximate Machine Unlearning for Privacy
inferred← citeshttps://doi.org/10.1109/iccworkshops67674.2025.11162281openalex-snapshot
Hierarchical Selection-Based Local Differential Privacy Federated Learning for Distributed Robotic Vehicle Collaboration with 6G
inferred← citeshttps://doi.org/10.1109/icih67754.2025.11609041openalex-snapshot
Secure and Scalable Federated Learning with Dynamic Trust Scoring and Anomaly-Resilient Aggregation
inferred← citeshttps://doi.org/10.1109/imcom69009.2026.11360927openalex-snapshot
Inversion, Membership, and Poisoning Attacks in Federated Learning - Challenges and Defenses
inferred← citeshttps://doi.org/10.1109/isqed69900.2026.11534734openalex-snapshot
A Data-Free Membership Inference Attack on Federated Learning in Hardware Assurance
inferred← citeshttps://doi.org/10.1109/iwcmc69287.2026.11579903openalex-snapshot
MAC-Unlearn: A Differentially Private Federated Edge Unlearning Framework to secure MAC De-randomization
inferred← citeshttps://doi.org/10.1109/jiot.2025.3627149openalex-snapshot
ADP-VRSGP: Decentralized Learning With Adaptive Differential Privacy via Variance-Reduced Stochastic Gradient Push
inferred← citeshttps://doi.org/10.1109/jiot.2026.3654994openalex-snapshot
pFedBlock: A Blockchain-Enhanced Split Federated Learning Framework for Robust and Traceable Model Training
inferred← citeshttps://doi.org/10.1109/jiot.2026.3720948openalex-snapshot
Federated Generation and Fusion for Privacy-Preserving Cross-Domain Optic Disc and Cup Segmentation in IoT-Enabled Healthcare
inferred← citeshttps://doi.org/10.1109/mita69365.2026.11582788openalex-snapshot
A Theoretically Grounded Differential Privacy Framework for Mitigating Membership Inference Risks in Federated Deep Learning
inferred← citeshttps://doi.org/10.1109/nnice68970.2026.11465223openalex-snapshot
Differentially Private Federated Learning with Adaptive Clipping Thresholds
inferred← citeshttps://doi.org/10.1109/qce65121.2025.00175openalex-snapshot
A Privacy-Preserving Federated Framework with Hybrid Quantum-Enhanced Learning for Financial Fraud Detection
inferred← citeshttps://doi.org/10.1109/smart66937.2025.11389477openalex-snapshot
Privacy-Preserving IAM in Hybrid Applications via Federated Learning
inferred← citeshttps://doi.org/10.1109/sp63933.2026.00205openalex-snapshot
Toward Efficient Membership Inference Attacks Against Federated Large Language Models: A Projection Residual Approach
inferred← citeshttps://doi.org/10.1109/tcc.2025.3620761openalex-snapshot
Model-Oriented Training With Two-Stage Hierarchical Knowledge Distillation Under Non-IID Conditions in Federated Edge–Cloud Collaboration
inferred← citeshttps://doi.org/10.1109/tcss.2026.3654406openalex-snapshot
Causal Inference-Based Collaborative Membership Inference Attack on Federated Recommendation
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3551921openalex-snapshot
RMR: A Relative Membership Risk Measure for Machine Learning Models
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3602908openalex-snapshot
SAMK: Secure Aggregation for Federated Learning Under Multiple Keys With Low Communication Rounds
inferred← citeshttps://doi.org/10.1109/tdsc.2026.3688036openalex-snapshot
EvaFL: An Efficient Verifiable Privacy-Preserving Federated Learning Against Malicious Servers
inferred← citeshttps://doi.org/10.1109/tits.2026.3687226openalex-snapshot
Bdes: Blockchain-Empowered Data and Energy Sharing in Internet of Electric Vehicles
inferred← citeshttps://doi.org/10.1109/tmc.2025.3623072openalex-snapshot
PRFL: Personalized and Robust Federated Learning for Non-IID Data With Malicious Participants
inferred← citeshttps://doi.org/10.1109/tmc.2026.3657229openalex-snapshot
FedShieldLLM: Measurement, Detection and Protection of Privacy Leakage in Federated LLMs
inferred← citeshttps://doi.org/10.1109/tmc.2026.3666356openalex-snapshot
Federated Unlearning via Distilled Data
inferred← citeshttps://doi.org/10.1109/ton.2025.3613505openalex-snapshot
PPVF: An Efficient Privacy-Preserving Online Video Fetching Framework With Correlated Differential Privacy
inferred← citeshttps://doi.org/10.1109/tpds.2026.3678282openalex-snapshot
Edge-End Heterogeneous Collaborative Learning by Prototype Selection and Edge Association
inferred← citeshttps://doi.org/10.1109/tps-isa67132.2025.00035openalex-snapshot
A Privacy-Fidelity Tradeoff Framework in Post-Processed Machine Learning
inferred← citeshttps://doi.org/10.1109/tsc.2025.3616355openalex-snapshot
BGTplanner: Maximizing Training Accuracy for Differentially Private Federated Recommenders via Strategic Privacy Budget Allocation
inferred← citeshttps://doi.org/10.1109/tsc.2026.3686323openalex-snapshot
FairWeight: Private Fairness-Aware Aggregation Using Model Interpretation Based Weightage in Federated Learning
inferred← citeshttps://doi.org/10.1109/tsc.2026.3686986openalex-snapshot
AdpFL: A Privacy-Preserving Federated Learning Framework Through Adaptive Model Pruning on Non-IID Data
inferred← citeshttps://doi.org/10.1109/vcc67261.2025.11351142openalex-snapshot
Assessing Privacy Risks in Differential Privacy Models for Communication-Centric Learning
inferred← citeshttps://doi.org/10.1111/trf.70418openalex-snapshot
The transformative power of artificial intelligence and machine learning in blood banking/transfusion medicine: A vein‐to‐vein approach from blood collection to transfusion services: On behalf of the AABB Foundation
inferred← citeshttps://doi.org/10.1145/3696410.3714711openalex-snapshot
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning
inferred← citeshttps://doi.org/10.1145/3696410.3714894openalex-snapshot
MER-Inspector: Assessing Model Extraction Risks from An Attack-Agnostic Perspective
inferred← citeshttps://doi.org/10.1145/3785353.3815094openalex-snapshot
Zero-Overhead Integrity Protection for Encrypted Federated Learning via Deterministic Self-Blinding
inferred← citeshttps://doi.org/10.1145/3795154.3795275openalex-snapshot
A Novel Chaotic-Map-Driven Privacy Protection Mechanism for Federated Learning
inferred← citeshttps://doi.org/10.1166/jno.2025.3854openalex-snapshot
High-Precision Photoelectric Detection of Wheel Hub Defects Using a Dual-Transfer Attention Mechanism Network for Optoelectronic Sensing Systems
inferred← citeshttps://doi.org/10.1177/14727978251374326openalex-snapshot
Application of graph neural networks (GNNs) in learning situation prediction and educational resource recommendation algorithms
inferred← citeshttps://doi.org/10.12720/jait.17.2.378-389openalex-snapshot
Benchmarking Federated Learning in Edge Computing Environments: A Systematic Review and Performance Evaluation
inferred← citeshttps://doi.org/10.1360/ssi-2025-0208openalex-snapshot
SDFL: a privacy-preserving Byzantine-robust decentralized federated learning scheme
inferred← citeshttps://doi.org/10.21203/rs.3.rs-9546424/v1openalex-snapshot
HeFLDPB: A Trustworthy Triple-Defence Architecture for Privacy-Preserving Collaborative Healthcare Fraud Detection
inferred← citeshttps://doi.org/10.21256/zhaw-35849openalex-snapshot
6G AI Security : from fundamentals to offensive and defensive landscape in 6G
inferred← citeshttps://doi.org/10.23919/splitech65624.2025.11091634openalex-snapshot
Bridging the Gap: Challenges and Limitations of Federated Learning in Real-World Applications
inferred← citeshttps://doi.org/10.33545/27076571.2023.v4.i2a.182openalex-snapshot
Privacy-preserving federated learning models for healthcare data
inferred← citeshttps://doi.org/10.3389/fpsyt.2026.1792429openalex-snapshot
Federated foundation models for psychiatry: a new paradigm for diagnosis, prognosis, and treatment of mood disorders
inferred← citeshttps://doi.org/10.3389/frai.2026.1914473openalex-snapshot
Data driven algorithmic advances in defect detection of additively manufactured materials using non-destructive testing: a review
inferred← citeshttps://doi.org/10.3390/ai7070264openalex-snapshot
Privacy-Preserving Federated Learning for Medical Image Classification with Selective Homomorphic Encryption
inferred← citeshttps://doi.org/10.3390/app16010500openalex-snapshot
Machine Learning Prediction of Pavement Macrotexture from 3D Laser-Scanning Data
inferred← citeshttps://doi.org/10.3390/cryst16060387openalex-snapshot
Yield Prediction Model for Ingot Samples Based on Machine Learning and Data Augmentation
inferred← citeshttps://doi.org/10.3390/designs10050090openalex-snapshot
AI-Driven Design and Optimization of a Federated Digital-Twin Architecture for Sustainable Self-Sensing Cementitious Infrastructure: A Physics-Based Synthetic Proof-of-Concept
inferred← citeshttps://doi.org/10.3390/electronics14102057openalex-snapshot
Utilisation of Artificial Intelligence and Cybersecurity Capabilities: A Symbiotic Relationship for Enhanced Security and Applicability
inferred← citeshttps://doi.org/10.3390/electronics14153016openalex-snapshot
Analysis of Student Progression Through Curricular Networks: A Case Study in an Illinois Public Institution
inferred← citeshttps://doi.org/10.3390/electronics14183692openalex-snapshot
Textile Defect Detection Using Artificial Intelligence and Computer Vision—A Preliminary Deep Learning Approach
inferred← citeshttps://doi.org/10.3390/info17090927openalex-snapshot
Time-Varying Privacy Scheduling for Communication-Efficient Differentially Private Federated Learning on Heterogeneous Educational Data
inferred← citeshttps://doi.org/10.3390/math13081296openalex-snapshot
Decentralized Federated Learning for Private Smart Healthcare: A Survey
inferred← citeshttps://doi.org/10.3390/math13152393openalex-snapshot
Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application
inferred← citeshttps://doi.org/10.3390/math13172769openalex-snapshot
YOLOv11-EMD: An Enhanced Object Detection Algorithm Assisted by Multi-Stage Transfer Learning for Industrial Steel Surface Defect Detection
inferred← citeshttps://doi.org/10.3390/s25206383openalex-snapshot
Integration of Machine Vision and PLC-Based Control for Scalable Quality Inspection in Industry 4.0
inferred← citeshttps://doi.org/10.3390/s26010229openalex-snapshot
A Systematic Review of Federated and Cloud Computing Approaches for Predicting Mental Health Risks
inferred← citeshttps://doi.org/10.3390/s26165297openalex-snapshot
Privacy-Preserving and Poisoning-Robust Federated Learning for Industrial IoT
inferred← citeshttps://doi.org/10.4018/979-8-3373-6224-3.ch007openalex-snapshot
Adversarial Robustness of Federated Learning in Healthcare
inferred← citeshttps://doi.org/10.4018/979-8-3373-6224-3.ch019openalex-snapshot
Legal and Policy Considerations in Adversarial Federated Learning
inferred← citeshttps://doi.org/10.4018/979-8-3373-9725-2.ch013openalex-snapshot
Artificial Intelligence–Driven Quality Inspection for Smart Manufacturing in Industry 4.0
inferred← citeshttps://doi.org/10.67808/jgidv1i1-001-260807110403openalex-snapshot
A Comprehensive Review of Privacy-Preserving Techniques in Federated Learning for IoT Networks
inferred← citeshttps://doi.org/10.7717/peerj-cs.3781openalex-snapshot
FedAugSec: a federated learning framework with data augmentation and selective encryption for financial fraud detection
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