federated learning

A Decentralized Learning Architecture for Medical Prescription Anomaly Detection via Hybrid Federated-Swarm Learning

The increasing use of electronic medical records (EMRs) has improved efficiency, accuracy, and accessibility of patient data. However, conventional centralized architectures suffer from single points of failure and data privacy issues. To address these challenges, this study proposes a decentralized machine learning ar...

PA-FedVL: A privacy-enhanced federated virtual learning framework based on label differential privacy distillation

Boosting Gradient-Based Training Diagnosis for Efficient and Accurate Federated Learning

Federated Learning (FL) allows edge clients to collaborate in model training with data privacy preserved, yet it is known to suffer low training efficiency and model accuracy. Given that efficiency and accuracy are usually conflicting objectives, existing practices increasingly employ an adaptive scheme that changes th...

STDFL: A Spatio-Temporal-Aware Dynamic Federated Learning Framework for Spatial Crowdsourcing

Spatial Mobile Crowdsourcing (SMC) faces the dual challenge of ensuring privacy while managing dynamic, Non-IID spatio-temporal data. While Federated Learning (FL) offers a privacy-preserving solution, traditional aggregation suffers from severe model drift due to evolving spatio-temporal contexts. Furthermore, existin...

Battery-Aware Dynamic Adaptive Low-Power Device Selection for IoT-Enabled FL Networks

The integration of Internet of Things (IoT) and Federated Learning (FL) marks a significant step towards pervasiveness, supported by distributed computational resources and enhanced by 5G advancements. However, the efficient and sustainable operation of IoT-enabled FL systems faces critical challenges, particularly in...

DPFL-GM: A dynamic privacy federated learning framework with gradual maturity mechanism

Differential photonic quantum memristor–modulated hopfield neural network with secure IoMT federated learning

Blockchain and Quantum FL-Based IDS for Security and Privacy of 6G-Enabled CE

The rapid proliferation of 6G-enabled consumer electronics (CE) has introduced significant security and privacy challenges. Traditional security mechanisms often fall short in addressing these issues due to the unique characteristics of CE networks. To enhance intrusion detection systems (IDSs), data-driven artificial...

Bilateral-verifiable and robust secure aggregation via TEE for asynchronous federated learning

Privacy-preserving video anomaly detection via federated learning

An analytics framework for privacy-preserving federated healthcare learning with quantum-inspired perturbation

IDADP: An information-driven agile framework for developing industrial AI tools based on blockchain-enabled federated learning