Authors
Parimala Boopalan, Swarna Priya Ramu, Quoc-Viet Pham, Kapal Dev, Praveen Kumar Reddy Maddikunta, Thippa Reddy Gadekallu, Thien Huynh-The
Publication date
2022/5/21
Source
Computer Networks
Pages
109048
Publisher
Elsevier
Description
Industrial Internet of Things (IIoT) lays a new paradigm for the concept of Industry 4.0 and paves an insight for new industrial era. Nowadays smart machines and smart factories use machine learning/deep learning based models for incurring intelligence. However, storing and communicating the data to the cloud and end device leads to issues in preserving privacy. In order to address this issue, Federated Learning (FL) technology is implemented in IIoT by the researchers nowadays to provide safe, accurate, robust and unbiased models. Integrating FL in IIoT ensures that no local sensitive data is exchanged, as the distribution of learning models over the edge devices has become more common with FL. Therefore, only the encrypted notifications and parameters are communicated to the central server. In this paper, we provide a thorough overview on integrating FL with IIoT in terms of privacy, resource and data …
Total citations
202120222023202421497751
Scholar articles
P Boobalan, SP Ramu, QV Pham, K Dev, S Pandya… - Computer Networks, 2022
QV Pham, K Dev, PKR Maddikunta, TR Gadekallu… - arXiv preprint arXiv:2101.00798, 2021
QV Pham, K Dev, PKR Maddikunta, TR Gadekallu - arXiv preprint arXiv:2101.00798
M Parimala, PRM Swarna, P Quoc-Viet, D Kapal… - Fusion of federated learning and industrial internet of …, 2022
M Parimala, RM Swarna Priya, QV Pham, K Dev… - Fusion of federated learning and industrial Internet of …, 2021