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Towards Quantifying Cross-Domain Maximal Extractable Value for Blockchain Decentralisation

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Information and Communications Security (ICICS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14252))

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Abstract

In the research society, many solutions to solving blockchain scaling have been tried historically, usually by compromising on decentralisation. Ethereum has chosen to scale by switching to Proof of Stake (PoS) consensus and adding data sharding to allow Layer 2 execution to be cheaper. However, in the light of cross-domain Maximal Extractable Value (MEV), even this strategy may have centralising forces built-in. In this work, we focus on cross domain MEV and try to identify cross domain arbitrage. We achieve this by extracting Uniswap data from four different domains and analysing the dataset with two different methods. Based on the analysis, we are successful in identifying one smart contract’s address, which is deployed to multiple domains, engaging in cross domain arbitrage. We also illustrate the difficulties when quantifying cross-domain MEV in practice.

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Notes

  1. 1.

    https://www.gnosis.io/.

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Acknowledgments

The dataset is available at https://sptage.compute.dtu.dk. This work was partially funded by the H2020 DataVaults project with GA Number 871755.

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Authors and Affiliations

  1. SPTAGE Lab, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark

    Johan Hagelskjar Sjursen, Weizhi Meng & Wei-Yang Chiu

Authors
  1. Johan Hagelskjar Sjursen
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  2. Weizhi Meng
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  3. Wei-Yang Chiu
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Corresponding author

Correspondence to Weizhi Meng .

Editor information

Editors and Affiliations

  1. Nankai University, Tianjin, China

    Ding Wang

  2. Columbia University, New York, NY, USA

    Moti Yung

  3. Nankai University, Tianjin, China

    Zheli Liu

  4. Xidian University, Xi’an, China

    Xiaofeng Chen

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Sjursen, J.H., Meng, W., Chiu, WY. (2023). Towards Quantifying Cross-Domain Maximal Extractable Value for Blockchain Decentralisation. In: Wang, D., Yung, M., Liu, Z., Chen, X. (eds) Information and Communications Security. ICICS 2023. Lecture Notes in Computer Science, vol 14252. Springer, Singapore. https://doi.org/10.1007/978-981-99-7356-9_37

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  • DOI: https://doi.org/10.1007/978-981-99-7356-9_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7355-2

  • Online ISBN: 978-981-99-7356-9

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