federated learning

V5GIDS: An ETSI NFV MANO-Aligned Federated Intrusion Detection Framework for 5G Networks

Experimental results show that V5GIDS achieves strong detection performance in the evaluated settings while improving deployment relevance through orchestration alignment, reduced telemetry exchange, and resource-aware distributed operation.

Adaptive feature fusion based semi-supervised federated learning system for ECG arrhythmia detection

Automatic cardiac arrhythmia detection using electrocardiogram (ECG) signals is essential for early diagnosis of cardiovascular conditions. Most of the previously existing systems for arrhythmia detection depend on fully supervised learning approaches. In addition to that, since the ECG patient data is centrally stored...

[Global Livingry Governance Architecture | Part 12]: Autonomous Tsunami Early Warning and Emergency Response System Architecture: Integration of Community Camera Networks, Subsea Station UAVs, Security Systems, Edge AI, and Tensor Stress Index (TSI_{t+1})

Disaster management and mitigation in coastal regions and tectonic fault zones require a fundamental shift from manual, expert-committee-dependent response models to closed-loop automated architectures. By combining the Tensor Stress Index function (TSI_{t+1}), Edge AI processing, distributed community observation netw...

FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation

Gastric cancer is one of the most commonly diagnosed cancers and has a high mortality rate. Due to limited medical resources, developing machine learning models for image-based gastric cancer recognition provides an efficient solution for medical institutions. However, such models typically require large sample sizes,...

Grand challenge in microbiome data science: recovering the microbiome as a system

The microbiome has never been only a census of organisms. In its original ecological formula4on, the term described a microbial community embedded in a defined habitat, with its own physicochemical condi4ons and "theatre of ac4vity" [1; 2]. That original framing is useful now because it reminds us that microbes do not...

SECURE FEDERATED INTRUSION DETECTION USING HOMOMORPHIC ENCRYPTION: A COMPARATIVE STUDY WITH ENSEMBLE LEARNING

The rapid growth of the Internet of Things (IoT) has also resulted in the increase of the demand in the intrusion detection systems, which can detect suspicious activity and keep the information confidential. The traditional centralized machine learning systems involve attaching the data of the distributed devices to a...

Optimizing resource allocation for federated LLM training via workload forecasting and autoscaling in edge environments

An integrated framework that combines LLM fine-tuning using federated adaptive local low-rank adaptation (FedALoRA) with forecasting-driven autoscaling policies is proposed, making it well-suited for federated-LLM Autoscaling in dynamic edge environments.

FedLLMsHydraNet: federated LLMs-driven model to enhance privacy-preserving and decision-making in financial credit risk prediction

A Novel Approach for Conducting Asynchronous Federated Learning with Blockchain Integration

Reputation-Driven Federated Learning: Enhancing Trust in Healthcare Data Sharing with Blockchain

Machine Learning and Blockchain in Peer-to-Peer Energy Trading: A Cross-Layer Review of Functional Roles, Market Operation, Trust, and Privacy

Peer-to-peer (P2P) energy trading combines local energy resources, market coordination, data-driven decisions, and transaction management. This review examines how machine learning (ML) and blockchain are used across these functions and separates market and ledger processes from physical electricity delivery. A structu...

AI in Predictive Healthcare II: A Ten-Domain Structured Evidence Review of Wearable Artificial Intelligence, 2024–2026

This expanded edition re-evaluates and extends a prior structured evidence review of artificial intelligence (AI) in wearable predictive healthcare. Where the original review verified evidence across four domains — atrial fibrillation, continuous glucose monitoring, federated learning and human digital twins — this edi...