Building Reliable IoT Ecosystems: A Generative AI-Enabled Federated Learning-Based Trust Management Approach
Din, Ikram Ud Almogren, Ahmad Han, Zhu Guizani, Mohsen
Din, Ikram Ud
Almogren, Ahmad
Han, Zhu
Guizani, Mohsen
Supervisor
Department
Machine Learning
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Type
Journal article
Date
2025
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Language
English
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Abstract
In the rapidly evolving domain of the Internet of Vehicles (IoV), ensuring robust trust management, privacy, and security presents significant challenges. This article proposes a novel approach integrating generative AI (GAI) and federated learning (FL) to address these challenges. FL allows distributed learning across vehicles without the need to share data, enhancing privacy compared to centralized methods. Our approach enhances trust management by raising the level of accuracy in detecting anomalies and preserving data privacy. As a result, the effectiveness of the proposed approach in practical real-world urban settings is illustrated by comprehensive evaluations using the CityPulse dataset. The results show a 20% improvement in trust scores under normal conditions, a 92% anomaly detection accuracy, and acceptable latency despite the added security measures. Additionally, 3-D visualizations illustrate the system’s robustness and scalability. This solution aligns with the objectives of 6G wireless communications, laying the groundwork for future intelligent, ultrareliable, and secure vehicular networks. Future research will focus on expanding the application of GAI and FL for real-time decision-making in large-scale IoV networks and optimizing cryptographic protocols.
Citation
I. Ud Din, A. Almogren, Z. Han and M. Guizani, "Building Reliable IoT Ecosystems: A Generative AI-Enabled Federated Learning-Based Trust Management Approach," in IEEE Internet of Things Journal, vol. 12, no. 10, pp. 13353-13366, 15 May15, 2025, doi: 10.1109/JIOT.2024.3511634
Source
IEEE INTERNET OF THINGS JOURNAL
Conference
Keywords
Blockchain security, Decentralized networks, Generative Artificial Intelligence (GAI), Internet of Vehicles (IoV), Trust management
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Publisher
IEEE