Print Email Facebook Twitter Protecting smart contracts of Decentralized Finance systems against Reentrancy attacks Title Protecting smart contracts of Decentralized Finance systems against Reentrancy attacks Author El Coudi El Amrani, Nafie (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Cyber Security) Contributor Ersoy, O. (mentor) Erkin, Z. (graduation committee) Urbano, Julián (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2021-07-01 Abstract Reentrancy attacks target smart contracts of Decentralized Finance systems that contain coding errors caused by developers. This type of attacks caused, in the past 5 years, the loss of over 400 million USD. Several countermeasures were developed that use patterns to detect reentrancy attacks on smart contracts before deployment on the Ethereum blockchain. However, the smart contracts are by default public and immutable once deployed on the blockchain. That is why the research question is: How can we protect smart contracts of DeFi systems deployed on the Ethereum blockchain that are known to be vulnerable to reentrancy attacks? A solution that detects reentrancy attacks on smart contracts after their deployment is presented in this paper. It flags transactions when a difference is found between the users' funds on both the application and protocol layers before and after each transaction using special made smart wallets. A proof of concept shows that the proposed solution can detect reentrancy attempts and stop them during the execution phase of smart contracts. Subject Reentrancy attacksDecentralized Finance SystemsSmart contracts To reference this document use: http://resolver.tudelft.nl/uuid:f641edcf-5695-4248-81c1-07084b196c9b Part of collection Student theses Document type bachelor thesis Rights © 2021 Nafie El Coudi El Amrani Files PDF CSE3000_ResearchProject_N ... Amrani.pdf 189.45 KB Close viewer /islandora/object/uuid:f641edcf-5695-4248-81c1-07084b196c9b/datastream/OBJ/view