federated learning

Auditable Federated Learning for Multimodal Brain Tumor Classification under Label Skew and Client Dropout

Toward Massive MIMO Receivers: Federated Learning under Adversarial Perturbation

Janus: Dual-Sided Communication and Privacy Optimization for Federated Learning in Autonomous Vehicles

To the authors' knowledge, this is the first vehicular-FL evaluation combining joint uplink-downlink compression with genuine HE-based privacy, validated through real cryptography, real privacy attacks, statistical testing, cross-dataset and cross-modality generalisation, and a convergence guarantee.

Noise-Perturbed Federated Learning for Synthetic Wearable Health Monitoring: A Reproducible Multi-Seed Evaluation

Privacy-Preserving Machine Learning Techniques for Cross-Sector Fraud Detection in the South African Financial and Telecommunications Sectors

Cross-sector fraud between South Africa’s financial and telecommunications sectors has intensified, driven by sophisticated criminal networks that exploit operational disparities between these industries. Traditional fraud detection systems, which depend on centralised data sharing and siloed organisational structures,...

Smart Agriculture and Environmental Monitoring: An Edge-AI, IoT, and Federated Learning Framework for Climate-Resilient Farming

This study presents a system architecture, algorithm, and evaluation protocol for smart agriculture and environmental monitoring. It is a method/architecture contribution and does not report field trial results. World food production is still under stress from climate variability, the availability of freshwater resourc...

Delay mitigation under data heterogeneity in decentralized federated learning

ETD-FGL: Federated Graph Learning Against Backdoor Attacks Using Topology-aware Defense

ETD-FGL: Federated Graph Learning Against Backdoor Attacks Using Topology-Aware Defense This release provides the research implementation of ETD-FGL, a topology-aware defense framework for investigating structural backdoor attacks in federated graph learning. The software includes experimental pipelines for the Cora, P...

Integrity Diagnostics for Cross-Silo Federated Deepfake Speech Detection Under Heterogeneity and Poisoning

Cross-silo deepfake speech detection must accommodate organizations that observe different attack profiles and channel conditions while avoiding routine centralization of raw speech. We study federated learning (FL) for a compact detector combining linear-frequency cepstral coefficients (LFCCs) with frozen WavLM repres...

THE EL-RAKHAWI THEORY OF COMPREHENSIVE LEGAL-TECH HARMONY Unifying AI, Digital Governance, and Socio-Environmental Justice into a Single Mathematical Framework for the 21st Century

The El-Rakhawi Theory of Comprehensive Legal-Tech Harmony unifies AI automation, digital governance, socio-legal stability, economic resilience, and environmental compliance as topological dimensions of a single legal-technological ecosystem. It introduces the Comprehensive Legal-Tech Harmony Index (CLTHI): CLTHI = (A_...

Federated Flight Anomaly Detection with Self-Supervised Forecasting: A Flight-Disjoint Evaluation

Reliable anomaly detection is essential for the safe operation of unmanned aerial vehicles (UAVs), particularly in distributed settings where flight telemetry is generated across multiple vehicles or operational sessions and cannot always be centrally collected. This work investigates UAV anomaly detection using models...

AI-Driven Genomic and Proteomic Insights in Dermatological Disorders

Dermatological disorders represent a massive global health burden, affecting approximately 2 billion people, yet conventional diagnosis often relies on morphology, leading to unpredictable, “trial-and-error” treatment. This necessitates a shift toward precision dermatology, leveraging the genomic and proteomic data tha...