PhD Topic: Organizational Modeling and Simulation of Blockchain Systems

Co-Supervisors: Önder Gürcan, Fabien Michel

Defense Date: 06 December 2024

Summary

Blockchain technology has gained substantial traction in recent years, revolutionizing industries through its decentralized and trustless nature. However, the security of blockchain systems and their underlying incentive mechanisms remains a critical concern. This thesis proposes a comprehensive framework using Multi-Agent Reinforcement Learning (MARL) to enhance the security of blockchain systems.

Key contributions include:

1. A generic organizational model for blockchain systems named AGR4BS.
2. A taxonomy of incentive vulnerabilities.
3. A role-based blockchain simulator compatible with MARL.

A detailed case study on Ethereum 2.0 is presented, highlighting practical applications of the proposed framework.

Report

• Hector Rousille, Organizational Modeling and Simulation of Blockchain Systems: A case study on blockchain vulnerabilities using Multi-Agent Reinforcement Learning, PhD Thesis, Université de Montpellier, 2024.
• Fabien Michel, Gauthier Picard, Hinde Bouziane, Önder Gürcan, Maria Potop-Butucaru, René Mandiau, Defence Report - PhD of Université de Montpellier, 2024.

Publications

• Hector Roussille, Önder Gürcan, Fabien Michel. Taxonomie des Vulnérabilités d’Incitations dans la Blockchain. 31èmes Journées Francophones sur les Systèmes Multi-Agents ( JFSMA 2023), Strassbourg, France, 5-7 July 2023.
• Hector Rousille, Önder Gürcan, Fabien Michel, A Taxonomy of Blockchain Incentive Vulnerabilities for Networked Intelligent Systems. In: IEEE Communications Magazine 61.8, pp. 108–114. DOI: 10.1109/MCOM.005.2200904.
• Hector Rousille, Önder Gürcan, Fabien Michel, AGR4BS: A Generic Multi-Agent Organizational Model for Blockchain Systems. In: Big Data and Cognitive Computing 6.1, 41p. ISSN: 2504-2289. doi: 10.3390/bdcc6010001.