FLIBD: A Federated Learning-Based IoT Big Data Management Approach for Privacy-Preserving over Apache Spark with FATE

FLIBD: A Federated Learning-Based IoT Big Data Management Approach for Privacy-Preserving over Apache Spark with FATE

In this study, we introduce FLIBD, a novel strategy for managing Internet of Things (IoT) Big Data, intricately designed to ensure privacy preservation across extensive system networks. By utilising Federated Learning (FL), Apache Spark, and Federated AI Technology Enabler (FATE), we skilfully inves...

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Bibliographic Details
Main Authors: Aristeidis Karras, Anastasios Giannaros, Leonidas Theodorakopoulos, George A. Krimpas, Gerasimos Kalogeratos, Christos Karras, Spyros Sioutas
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Electronics
Subjects:
federated learning
privacy preserving
data poisoning
Big Data systems
Apache Spark
FATE
Online Access:https://www.mdpi.com/2079-9292/12/22/4633

Internet

https://www.mdpi.com/2079-9292/12/22/4633

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