federated learning

Secure Design Principles for AI-Driven Learning Platforms

Artificial intelligence is increasingly integrated into educational tools such as learning management systems, analytics dashboards, adaptive assessment services, and generative AI assistants. These platforms support personalized learning and institutional decision-making, but they create risks linked to digital identi...

Federated Learning and Edge Computing in Advanced Communications

QoS-Aware Secure Federated Intelligence for Biomedical Electronics and Medical Informatics in Wireless Health Monitoring Networks

Wireless Health Monitoring Networks (WHMNs) that utilize Biomedical Electronics (BMEs) are rapidly changing how medical information is gathered and used in contemporary Medical Informatics through providing ongoing, real-time, and remote assessment and monitoring of essential physiological parameters; including electro...

ADVANCES IN AI-BASED PERSONALIZED HEALTHCARE

Artificial intelligence (AI) is increasingly changing the way healthcare is delivered by supporting a more personalized and patient-centered approach to medicine. Personalized medicine combines information such as genetics, genomics, medical history, lifestyle, laboratory results, medical images, and continuous health...

Adaptive federated ensemble learning with hyperparameter optimization for distributed healthcare IoT

The rapid evolution of IoT-enabled healthcare systems has resulted in large-scale distributed data generation across various institutions. While federated learning enables collaborative model training without centralized data, it degrades non-identical data distributions and statistical imbalance across clients. Moreov...

Differential Privacy Synthetic Tabular Data Generation for Federated Learning

Machine learning in healthcare struggles for one main reason: good data are hard to come by. Medical records are sensitive, and the rules on sharing them between hospitals are strict. A common workaround is the use of synthetic data, that is, artificial records that copy the statistics of real ones; however, on its own...

FLCore

Federated Learning benchmark of classical machine learning models.

FedHEAL-IoMT: A Federated Hierarchical Evidential Adaptive Learning Framework for Zero-day DDoS Detection in Internet of Medical Things Networks

Distributed denial-of-service (DDoS) traffic dominates the attack taxonomy of current Internet of Medical Things (IoMT) testbeds, and federated learning (FL) has become the accepted way of training detectors without moving patient-adjacent traffic off hospital premises.Existing federated IoMT detectors nevertheless com...

A Comparative Study of Client-Level Stabilization Techniques in Federated Learning for Robust Plant Disease Recognition

The successful integration of artificial intelligence (AI) algorithms in precision agriculture provided farmers with the means to identify potential issues, such as early disease detection or pest infestations, by making crop-related predictions. The new technological developments in this field improve the functioning...

Distributed Artificial Intelligence for Privacy Preservation and Cyber Resilience in Educational Ecosystems

The digitization of education has concentrated vast volumes of sensitive learner data within centralized platforms that are priority targets for cyber attackers. It is argued that the dominant centralized model of educational artificial intelligence is structurally misaligned with modern privacy and resilience needs, a...

Federated learning with attention-based CNN-LSTM encoders and decoders for adaptive risk aggregation in internet of vehicles (IoV)

Trustworthy Federated Learning for Cybersecurity: A Three-Level Assurance Taxonomy, Design-Space Audit, and Source-Linked Critical Review.

This repository contains the supporting evidence and reproducibility materials for the manuscript “Trustworthy Federated Learning for Cybersecurity: A Three-Level Assurance Taxonomy, Design-Space Audit, and Source-Linked Critical Review.” The package includes: A study-feature matrix covering 20 studies and 18 features....