Securing IoT With Deep Federated Learning: A Trust-Based Malicious Node Identification Approach
The Internet of Things (IoT) has revolutionized the world with its diverse applications and smart connected devices. These IoT devices communicate with each other without human intervention and make life easier in many ways. However, the independence of these devices raises several significant conce...
Main Authors: | Kamran Ahmad Awan, Ikram Ud Din, Mahdi Zareei, Ahmad Almogren, Byung Seo-Kim, Jesus Arturo Perez-Diaz |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10147216/ |
Similar Items
-
Enhancing IoT Security With Trust Management Using Ensemble XGBoost and AdaBoost Techniques
by: Kamran Ahmad Awan, et al.
Published: (2024-01-01) -
MicroTrust: Empowering Microgrids With Smart Peer-to-Peer Energy Sharing Through Trust Management in IoT
by: Wajahat Ali, et al.
Published: (2024-01-01) -
vTrust: An IoT-Enabled Trust-Based Secure Wireless Energy Sharing Mechanism for Vehicular Ad Hoc Networks
by: Kamran Ahmad Awan, et al.
Published: (2021-11-01) -
Blockchain-Based Trust and Authentication Model for Detecting and Isolating Malicious Nodes in Flying Ad Hoc Networks
by: Kashif Naseer Qureshi, et al.
Published: (2024-01-01) -
Privacy-Preserving Big Data Security for IoT With Federated Learning and Cryptography
by: Kamran Ahmad Awan, et al.
Published: (2023-01-01)