Privacy concerns and the increasing demand for secure and efficient continuous authentication have underscored the necessity of decentralized solutions. This thesis aims to develop advanced privacy-preserving techniques for continuous user authentication while addressing resource optimization and client selection challenges in decentralized systems. By tackling issues such as resource efficiency, scalability, and secure client participation, this research enhances the practicality and performance of decentralized authentication mechanisms in real-world scenarios.
The contributions of this research are threefold:
1. Development of a decentralized privacy-preserving framework: This framework ensures user data confidentiality while achieving high authentication accuracy.
2. Adaptive client selection mechanism: The proposed mechanism optimizes resource usage and prioritizes the participation of reliable clients.
3. Resource optimization strategies: These strategies improve the efficiency and scalability of the decentralized system, facilitating seamless operations across diverse environments and devices.
The proposed approaches are validated through extensive experimentation using real-world datasets, demonstrating notable advancements in resource utilization, authentication accuracy, and system scalability. These contributions provide a strong foundation for privacy-preserving decentralized systems, enabling their practical application in Internet of Things (IoT) environments and other domains.
| Date | 9 Mar 2025 |
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| Original language | American English |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Chamseddine Talhi (Supervisor) & Azzam Mourad (Co-supervisor) |
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Wazzeh, M. (Author),
Talhi (Supervisor) & Mourad (Co-supervisor),
9 Mar 2025Student thesis: Doctoral thesis › Doctorate in Engineering: Engineering