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Smart Contract vulnerabilities affecting Federated Learning’s privacy guarantees
Awadhpersad, P.S. (2025) Smart Contract vulnerabilities affecting Federated Learning’s privacy guarantees.
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| Abstract: | Blockchain-based Federated Learning (BCT-FL) integrates blockchain technology with Federated Learning (FL) to enhance privacy, trust, and auditability. The use of smart contracts in this integration raises the discussion of their documented vulnerabilities and their relevance to FL. This paper examines the impact of smart contract vulnerabilities on the privacy guarantees of BCT-FL systems. It provides a structured taxonomy of vulnerabilities based on trusted sources, maps their effects on key privacy preserving mechanisms(e.g., secure aggregation, differential privacy, certificate-less authentication), and analyzes their severity through a custom evaluation framework. The findings highlight that certain vulnerability classes, such as access control flaws, improper exception handling, and storage design issues, pose a critical threat to confidentiality and trust. It concludes with a discussion on the framework used and recommends directions for privacy-aware smart contract design, specifically tailored to the needs of Federated Learning systems. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Business & IT BSc (56066) |
| Link to this item: | https://purl.utwente.nl/essays/107369 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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