federated learning

Privacy-Preserving Federated Learning for Industrial Supply Chains via Dynamic Masking and Quality-Aware Secure Aggregation

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Dual-angle perception partition aggregation federated learning for multi-center multi-modality contrast-free liver tumor segmentation

Uncertainty-aware Bayesian federated learning for low-resource neural machine translation at the edge

Edge translation systems must balance limited computation, data locality, and weak performance on low-resource language pairs. This study presents Multitask Bayesian Federated Learning (MT-BayesFL), a multilingual translation framework that combines a lightweight shared encoder, task-specific decoders, matrix-normal po...

Artificial Intelligence-Based Intelligent Fertigation Recommendation Systems for Precision Agriculture

Artificial-intelligence-enabled fertilizer and fertigation recommendation has progressed from single-task crop or fertilizer classification toward integrated decision-support architectures. However, predictive classification, agronomic dose calculation, irrigation scheduling, explainability, real-time sensing, and farm...

A Spatio-Temporal Transformer-Based Approach for Network Attack Detection

With the proliferation of dynamic network environments such as the Internet of Things (IoT) and Vehicle-to-Everything (V2X) networks, challenges related to data localization and privacy leakage have become increasingly prominent. Efficient and privacy-preserving real-time network attack detection has emerged as a criti...

Secure Healthcare Data Analytics for Early Disease Detection: Cybersecurity and Big Data Solutions

This article looks at secure methods for healthcare data analytics leveraging big data technologies in conjunction with advanced cybersecurity methods, including encryption, blockchain, federated learning, and artificial intelligence (AI) models which help ensure patient data remain protected while providing predictive...

VCFedAdam: A Verifiable and Compressed FedAdam Aggregation Scheme for Federated Learning in Distributed Sensor Networks

Experimental results show that VCFedAdam reduces computation overhead by 90.25% and communication overhead by 75.38% compared with traditional secure aggregation, and security analysis confirms that VCFedAdam achieves both privacy protection and aggregation verifiability.

Robust detection method for adversarial backdoor attacks under federated learning architecture

A robust detection method featuring a two layer "norm verification + directional consistency" filtering mechanism combined with the Isolation Forest algorithm to remove malicious outliers, a weighted adaptive robust aggregation that dynamically allocates weights based on client accuracy and consistency, updates the glo...

"Buffalo and Cattle Characteristics Census Survey Dataset 2026"

"Buffalo and Cattle Characteristics Census Survey Dataset 2026 is a synthetic livestock research dataset containing 500 animal-level records and 79 attributes representing buffalo and cattle characteristics relevant to livestock management and animal husbandry research. The dataset incorporates geographical, breed, dem...

Human-centered design based on federated learning to optimize user experience on blockchain platforms

In modern decentralized environments, designing systems that are not only efficient and secure but also understandable and trustworthy for end-users has emerged as the central challenge. Blockchain and Federated Learning (FL) have become two seminal technologies that facilitate privacy-preserving and transparent proces...

Privacy-Preserving Federated Learning for Industrial Supply Chains via Dynamic Masking and Quality-Aware Secure Aggregation

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FAIRVAR: Fair Federated Learning via Variance Regularization