2020/03/08 by Kaihua Qin, Liyi Zhou, Qin, Kaihua +5 · 1 voice · 41 citations
Computer Science · #Arbitrage #Atomicity #Blockchain Technology Applications and Security #Business #Collateral #Computer science #Database transaction #Debt #Economics #Finance #Loan #Microeconomics #Profit (economics) #Revenue #cs.CR #cs.DC
paper · pdf · doi:10.48550/arxiv.2003.03810
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2020/03/08 · arxiv published 2020/03/08 · arxiv created 2021/03/20 · arxiv updated 2021/03/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Credit allows a lender to loan out surplus capital to a borrower. In the traditional economy, credit bears the risk that the borrower may default on its debt, the lender hence requires upfront collateral from the borrower, plus interest fee payments. Due to the atomicity of blockchain transactions, lenders can offer flash loans, i.e., loans that are only valid within one transaction and must be repaid by the end of that transaction. This concept has lead to a number of interesting attack possibilities, some of which were exploited in February 2020. This paper is the first to explore the implication of transaction atomicity and flash loans for the nascent decentralized finance (DeFi) ecosystem. We show quantitatively how transaction atomicity increases the arbitrage revenue. We moreover analyze two existing attacks with ROIs beyond 500k%. We formulate finding the attack parameters as an optimization problem over the state of the underlying Ethereum blockchain and the state of the DeFi ecosystem. We show how malicious adversaries can efficiently maximize an attack profit and hence damage the DeFi ecosystem further. Specifically, we present how two previously executed attacks can be "boosted" to result in a profit of 829.5k USD and 1.1M USD, respectively, which is a boost of 2.37x and 1.73x, respectively.