federated learning

Robust Federated Learning for Detecting False Data Injection Attacks in Advanced Metering Infrastructure under Non-IID Data — Source Code

This repository contains the complete source code for the paper "Robust Federated Learning for Detecting False Data Injection Attacks in Advanced Metering Infrastructure under Non-IID Data." The framework couples a lightweight two-branch GRU local detector with a server-side robust aggregation pipeline (per-client EMA...

PhysGuard-FL: Reproducibility package for physics-aware Byzantine-robust federated learning in chemical process monitoring

Complete research compendium for PhysGuard-FL, a physics-aware Byzantine-robust federated-learning framework evaluated for chemical-process monitoring. The frozen benchmark uses six Tennessee Eastman Process operating modes, 20 federated clients, 20 communication rounds, five local steps, and 10 matched random seeds. T...

Privacy-Preserving Federated Learning for Cross-Border Data Flows in Uganda: Robustness Under Distribution Shift and Sparse Labels

Cross-border data flows are central to Uganda's digital economy, yet their governance is complicated by competing pressures: the need for international integration and the legal obligation to protect citizen privacy. Federated learning offers a promising architecture for training machine learning models across distribu...

MAFL-PdM: A Multi-Agent Federated Learning Framework for Personalised Predictive Maintenance Across Heterogeneous Industrial IoT Sites

A Multi-Layer Auditable Vertical Federated Learning Prototype for Power Equipment Supply Chains: Reproducibility, Robustness, and Privacy-Boundary Evaluation

Transformer lifecycle data across organizations are typically vertically partitioned among material suppliers, manufacturers, logistics service providers, testing agencies, and operation and maintenance units. This study presents a reproducible multi-layer vertical federated learning (VFL) prototype that integrates sal...

Privacy-Preserving Federated Learning for Cryptography Cybersecurity in Uganda: Robustness Under Distribution Shift and Sparse Labels

The federated monitoring of cryptographic failure and cyber-intrusion signals across Ugandan institutions inherits two under-addressed tensions: client event distributions drift with sectoral traffic, software configuration and adversary behaviour, and attack labels remain sparse because cryptographic incident confirma...

Decentralized Vertical Federated Learning via Graph-Based Learning Consensus

Federated deep learning and digital-twin optimization for cyber-resilient smart nano grid energy management

Chain-Resilience: A Blockchain-Based Federated Continual Learning Framework for Defending Against Forgetting and Distrust

ADAX-FED: Adaptive and Explainable Federated Learning for Residential Network Load Forecasting

IoT-Based Elderly Health Monitoring Information System with Federated Learning for Early Health Risk Prediction

The increasing elderly population in Indonesia has contributed to a higher prevalence of non-communicable diseases, including hypertension, cardiovascular disease, diabetes mellitus, and chronic obstructive pulmonary disease (COPD). This trend highlights the need for continuous, real-time health monitoring rather than...

FedLR: A federated learning based approach for faster communication in edge environment

A new approach, FedLR, is proposed in this manuscript to remedy the problem of slacker devices, which provides all the benefits of FedAvg while reducing the communication costs between the devices.