Boosting Privately: Federated Extreme Gradient Boosting for Mobile Crowdsensing

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SecureBoost: A Lossless Federated Learning Framework

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When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning

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Lightweight Privacy-Preserving Ensemble Classification for Face Recognition

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Analyzing gender inequality through large-scale Facebook advertising data

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A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic RegressionPreprint

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Oblivious Mechanisms in Differential Privacy: Experiments, Conjectures, and Open Questions

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Federated Learning for Internet of Things: A Comprehensive Survey

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Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey

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Federated Deep Learning for Cyber Security in the Internet of Things: Concepts, Applications, and Experimental Analysis

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Efficiency Optimization Techniques in Privacy-Preserving Federated Learning With Homomorphic Encryption: A Brief Survey

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FedOpt: Towards Communication Efficiency and Privacy Preservation in Federated Learning

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Federated Learning for Industrial Internet of Things in Future Industries

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Applications of Federated Learning; Taxonomy, Challenges, and Research Trends

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Semisupervised Federated-Learning-Based Intrusion Detection Method for Internet of Things

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Challenges, Applications and Design Aspects of Federated Learning: A Survey

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Privacy-Preserving Aggregation in Federated Learning: A Survey

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ELSA: Secure Aggregation for Federated Learning with Malicious Actors

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CrowdFL: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning

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Privacy-preserving edge federated learning for intelligent mobile-health systems

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A review on federated learning towards image processing

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Applications of Distributed Machine Learning for the Internet-of-Things: A Comprehensive Survey

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Federated learning meets blockchain at 6G edge

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Natural Language Processing Applications for Computer-Aided Diagnosis in Oncology

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PrivacyEAFL: Privacy-Enhanced Aggregation for Federated Learning in Mobile Crowdsensing

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An Efficient Learning Framework for Federated XGBoost Using Secret Sharing and Distributed Optimization

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Extremely Randomized Trees With Privacy Preservation for Distributed Structured Health Data

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A Critical Evaluation of Privacy and Security Threats in Federated Learning

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A Survey on the use of Federated Learning in Privacy-Preserving Recommender Systems

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Collaborative Machine Learning: Schemes, Robustness, and Privacy

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Edge intelligence secure frameworks: Current state and future challenges

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Multi-party Diabetes Mellitus risk prediction based on secure federated learning

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Joint Optimization of Energy Consumption and Completion Time in Federated Learning

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Privacy preserving and secure robust federated learning: A survey

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Energy-Efficient and Privacy-Preserved Incentive Mechanism for Mobile Edge Computing-Assisted Federated Learning in Healthcare System

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Power of Redundancy: Surplus Client Scheduling for Federated Learning Against User Uncertainties

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Decision Tree-Based Federated Learning: A Survey

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A Hybrid Federated Learning Framework With Dynamic Task Allocation for Multi-Party Distributed Load Prediction

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An Overview of Trustworthy AI: Advances in IP Protection, Privacy-preserving Federated Learning, Security Verification, and GAI Safety Alignment

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Boosting the Federation: Cross-Silo Federated Learning without Gradient Descent

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A Review of Research on Secure Aggregation for Federated Learning

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SHFL: K-Anonymity-Based Secure Hierarchical Federated Learning Framework for Smart Healthcare Systems

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A Cooperative Analysis to Incentivize Communication-Efficient Federated Learning

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Advancing Federated Learning: A Systematic Literature Review of Methods, Challenges, and Applications

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Edge Resource Prediction and Auction for Distributed Spatial Crowdsourcing With Differential Privacy

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AI-empowered mobile edge computing: inducing balanced federated learning strategy over edge for balanced data and optimized computation cost

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Reduction in Data Imbalance for Client-Side Training in Federated Learning for the Prediction of Stock Market Prices

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QARMA-FL: Quality-Aware Robust Model Aggregation for Mobile Crowdsourcing

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Tree-Based Models for Federated Learning Systems

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Achieving privacy-preserving cross-silo anomaly detection using federated XGBoost

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Efficient and Privacy-Preserving Outsourcing of Gradient Boosting Decision Tree Inference

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Leveraging federated learning and edge computing for pandemic-resilient healthcare

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XORBoost: Tree Boosting in the Multiparty Computation Setting

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Introduction to Federated Learning

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FedXGBoost: Privacy-Preserving XGBoost for Federated LearningPreprint

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Lattice based distributed threshold additive homomorphic encryption with application in federated learning

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A privacy-preserving multi-agent updating framework for self-adaptive tree model

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Lightweight Privacy-Preserving Federated Incremental Decision Trees

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Pooling critical datasets with Federated Learning

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Malicious Participants and Fake Task Detection Incorporating Gaussian Bias

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A Distributed Threshold Additive Homomorphic Encryption for Federated Learning with Dropout Resiliency Based on Lattice

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Label Noise Correction for Federated Learning: A Secure, Efficient and Reliable Realization

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Adversarial Machine Learning-Driven Fake Task Anticipation in Mobile Crowdsensing Systems

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FedVoting: A Cross-Silo Boosting Tree Construction Method for Privacy-Preserving Long-Term Human Mobility Prediction

Liu, Y., Fan, Z., Song, X., & Shibasaki, R. (2021) · Sensors · doi:10.3390/s21248282 · Cited by 7 · see citing works

Existing Privacy Protection Solutions

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Optimizing Urban Traffic Incident Prediction With Vertical Federated Learning: A Feature Selection Based Approach

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Protecting Against Data Leakage in Federated Learning: What Approach Should You Choose?

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A fair and verifiable federated learning profit-sharing scheme

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Scalable and Secure Federated XGBoost

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Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization

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Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science

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Generative Adversarial Network-Driven Detection of Adversarial Tasks in Mobile Crowdsensing

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SoK: Privacy-Preserving Collaborative Tree-based Model Learning

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An Efficient Speculative Federated Tree Learning System With a Lightweight NN-Based Predictor

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Privacy-Preserving Detection of Poisoning Attacks in Federated Learning

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Toward Efficient and End-to-End Privacy-Preserving Distributed Gradient Boosting Decision Trees

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Federated Learning with Differential Privacy and an Untrusted Aggregator

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SAEV: Secure Aggregation and Efficient Verification for Privacy-Preserving Federated Learning

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A two-tiered incentive mechanism design for federated crowd sensing

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Gradient Boosting Forest: a Two-Stage Ensemble Method Enabling Federated Learning of GBDTs

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Federated Learning at Mobile Edge Networks: A Tutorial

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Machine Learning for Privacy Threat Classification: A Systematic ReviewPreprint

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An Empirical Study on Security Methods for Federated Learning Environments and Their Various Applications

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BVSAP: A Bidirectional Verifiable Secure Aggregation Protocol for federated learning

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MSCS: Multi-task Secure Aggregation with Cosine Similarity for Federated Learning in Mobile Crowdsensing

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Federated Inter-Bank Default Prediction: Enabling Secure Credit Risk Assessment Without Data Sharing

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A Comprehensive Review on Federated and Incremental Learning in Spatial Crowdsourcing Systems

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Scalable and Efficient Security Solutions for IoT Networks: An Adaptive Machine Learning Approach

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Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing

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Secure Federated XGBoost with CUDA-Accelerated Homomorphic Encryption via NVIDIA FLARE

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BlindFL: Segmented Federated Learning with Fully Homomorphic EncryptionPreprint

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