federated learning

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....

AI-Driven Next-Generation DDoS Mitigation in IoT: A Comprehensive Survey of Deep Learning and Large Language Models

The global Internet of Things (IoT) network has experienced unprecedented expansion, reaching 75.44 billion connected devices worldwide. Due to this rapid growth, the IoT ecosystem has become larger but also more vulnerable to various threats in cyberspace. As a result, this situation has accelerated the development of...

A review of recent advances in privacy-preserving federated learning for healthcare applications

The rapid adoption of artificial intelligence (AI) in healthcare, driven by the increasing availability of electronic health records (EHRs), medical imaging systems, genomic data, and wearable devices, has created significant challenges related to patient privacy, data security, and regulatory compliance. Traditional c...

A systematic review of federated learning based intrusion detection systems in software defined networking

FedPoP: federated learning meets proof of participation

Federated learning (FL) offers privacy preserving, distributed machine learning, allowing clients to contribute to a global model without revealing their local data. As models increasingly serve as monetizable digital assets, the ability to prove participation in their training becomes essential for establishing owners...