Maximizing Extractable Value from Automated Market Makers

Massimo Bartoletti; James Hsin yu Chiang; Alberto Lluch Lafuente

doi:10.1007/978-3-031-18283-9_1

Maximizing Extractable Value from Automated Market Makers

Massimo Bartoletti, James Hsin yu Chiang^*, Alberto Lluch Lafuente

^*Corresponding author for this work

University of Cagliari

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

Automated Market Makers (AMMs) are decentralized applications that allow users to exchange crypto-tokens without the need for a matching exchange order. AMMs are one of the most successful DeFi use cases: indeed, major AMM platforms process a daily volume of transactions worth USD billions. Despite their popularity, AMMs are well-known to suffer from transaction-ordering issues: adversaries can influence the ordering of user transactions, and possibly front-run them with their own, to extract value from AMMs, to the detriment of users. We devise an effective procedure to construct a strategy through which an adversary can maximize the value extracted from user transactions.

Original language	English
Title of host publication	Financial Cryptography and Data Security
Editors	Ittay Eyal, Juan Garay
Publisher	Springer
Publication date	2022
Pages	3-19
ISBN (Print)	9783031182822
DOIs	https://doi.org/10.1007/978-3-031-18283-9_1
Publication status	Published - 2022
Event	25th International Conference on Medical Image Computing and Computer-Assisted Intervention - Resorts World Convention Centre Singapore, Singapore, Singapore Duration: 18 Sept 2022 → 22 Sept 2022 Conference number: 25 https://conferences.miccai.org/2022/en/

Conference

Conference	25th International Conference on Medical Image Computing and Computer-Assisted Intervention
Number	25
Location	Resorts World Convention Centre Singapore
Country/Territory	Singapore
City	Singapore
Period	18/09/2022 → 22/09/2022
Internet address	https://conferences.miccai.org/2022/en/

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13411 LNCS
ISSN	0302-9743

Keywords

Decentralized finance
Front-running
Miner extractable value

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10.1007/978-3-031-18283-9_1

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Bartoletti, Massimo ; Chiang, James Hsin yu ; Lluch Lafuente, Alberto. / Maximizing Extractable Value from Automated Market Makers. Financial Cryptography and Data Security. editor / Ittay Eyal ; Juan Garay. Springer, 2022. pp. 3-19 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13411 LNCS).

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Bartoletti, M, Chiang, JHY & Lluch Lafuente, A 2022, Maximizing Extractable Value from Automated Market Makers. in I Eyal & J Garay (eds), Financial Cryptography and Data Security. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13411 LNCS, pp. 3-19, 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, Singapore, Singapore, 18/09/2022. https://doi.org/10.1007/978-3-031-18283-9_1

Maximizing Extractable Value from Automated Market Makers. / Bartoletti, Massimo; Chiang, James Hsin yu; Lluch Lafuente, Alberto.
Financial Cryptography and Data Security. ed. / Ittay Eyal; Juan Garay. Springer, 2022. p. 3-19 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13411 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Lluch Lafuente, Alberto

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N2 - Automated Market Makers (AMMs) are decentralized applications that allow users to exchange crypto-tokens without the need for a matching exchange order. AMMs are one of the most successful DeFi use cases: indeed, major AMM platforms process a daily volume of transactions worth USD billions. Despite their popularity, AMMs are well-known to suffer from transaction-ordering issues: adversaries can influence the ordering of user transactions, and possibly front-run them with their own, to extract value from AMMs, to the detriment of users. We devise an effective procedure to construct a strategy through which an adversary can maximize the value extracted from user transactions.

AB - Automated Market Makers (AMMs) are decentralized applications that allow users to exchange crypto-tokens without the need for a matching exchange order. AMMs are one of the most successful DeFi use cases: indeed, major AMM platforms process a daily volume of transactions worth USD billions. Despite their popularity, AMMs are well-known to suffer from transaction-ordering issues: adversaries can influence the ordering of user transactions, and possibly front-run them with their own, to extract value from AMMs, to the detriment of users. We devise an effective procedure to construct a strategy through which an adversary can maximize the value extracted from user transactions.

KW - Decentralized finance

KW - Front-running

KW - Miner extractable value

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DO - 10.1007/978-3-031-18283-9_1

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Bartoletti M, Chiang JHY, Lluch Lafuente A. Maximizing Extractable Value from Automated Market Makers. In Eyal I, Garay J, editors, Financial Cryptography and Data Security. Springer. 2022. p. 3-19. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13411 LNCS). doi: 10.1007/978-3-031-18283-9_1