A Comprehensive Survey on Federated Learning in the Healthcare Area: Concept and Applications.

D Upreti, E Yang, H Kim, C Seo - … -Computer Modeling in …, 2024 - search.ebscohost.com
Federated learning is an innovative machine learning technique that deals with centralized
data storage issues while maintaining privacy and security. It involves constructing machine …

Advanced intrusion detection in MANETs: A survey of machine learning and optimization techniques for mitigating black/gray hole attacks

SM Hassan, MM Mohamad, FB Muchtar - IEEE Access, 2024 - ieeexplore.ieee.org
Mobile Ad Hoc Networks (MANETs) are dynamic networks without fixed infrastructure,
making them particularly vulnerable to security threats such as black and gray hole attacks …

ESVFL: Efficient and secure verifiable federated learning with privacy-preserving

J Cai, W Shen, J Qin - Information Fusion, 2024 - Elsevier
Federated learning has been widely applied as a distributed machine learning method in
various fields, allowing a global model to be trained by sharing local gradients instead of …

An efficient model of enhanced optimization and dilated-GRU based secured multi-access edge computing with blockchain for VANET sector

L Kalidoss, S Thouti, R Arunachalam… - Expert Systems with …, 2025 - Elsevier
Abstract The establishment of Vehicular Ad Hoc Networks (VANETs) has brought significant
advantages to humans, yet it also raises crucial safety considerations. Security is one of the …

Enhancing MANET Security through Federated Learning and Multiobjective optimization: A Trust-aware Routing Framework

SM Hassan, MM Mohamad, FB Muchtar… - IEEE …, 2024 - ieeexplore.ieee.org
Mobile ad hoc networks (MANETs) face significant challenges in maintaining secure and
efficient communication owing to their dynamic nature and vulnerability to security threats …

A multifaceted survey on federated learning: Fundamentals, paradigm shifts, practical issues, recent developments, partnerships, trade-offs, trustworthiness, and ways …

A Majeed, SO Hwang - IEEE Access, 2024 - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …

A secure object detection technique for intelligent transportation systems

MJ Mia, MH Amini - IEEE Open Journal of Intelligent …, 2024 - ieeexplore.ieee.org
Federated Learning is a decentralized machine learning technique that creates a global
model by aggregating local models from multiple edge devices without a need to access the …

An authentication protocol for federated learning with blockchain in consumer electronic assisted autonomous driving environments

CM Chen, Y Hao, S Kumari… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Consumer electronics play a crucial role in the automotive sector by providing the essential
hardware infrastructure necessary for develo** autonomous vehicles. These vehicles …

Review of Mathematical Optimization in Federated Learning

S Yang, F Zhao, Z Zhou, L Shi, X Ren, Z Xu - arxiv preprint arxiv …, 2024 - arxiv.org
Federated Learning (FL) has been becoming a popular interdisciplinary research area in
both applied mathematics and information sciences. Mathematically, FL aims to …

CLDP-FATD: Secure Federated Averaging Threat Detection Framework for IVSN Based on Client-Level Differential Privacy

GO Anyanwu, H Karimipour - IEEE Internet of Things Journal, 2025 - ieeexplore.ieee.org
The certification of real-time information in vehicles is contingent upon threat detection.
Intelligent Vehicle Sensor Networks (IVSN) have revolutionized modern transportation …