Abstract
Manipulation of user transactions by miners in permissionless blockchain systems is a growing concern. This problem is a pervasive and systemic issue that incurs high costs for users of decentralised applications and is known as Miner Extractable Value (MEV). Furthermore, transaction manipulations create other issues such as congestion, higher fees, and system instability. Detecting transaction manipulations is difficult, even though it is known that they originate from the pre-consensus phase of transaction selection for building blocks, at the base layer of blockchain protocols. In this paper, we summarize known transaction manipulation attacks. We present LO, an accountable base layer protocol designed to detect and mitigate transaction manipulations. LO is built around the accurate detection of transaction manipulations and assignment of blame at the granularity of a single mining node. LO forces miners to log all the transactions they receive into a secure mempool data structure and to process them in a verifiable manner. Overall, LO quickly and efficiently detects censorship, injection or re-ordering attempts. Our performance evaluation shows that LO is also practical and only introduces a marginal performance overhead.
Original language | English |
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Title of host publication | Middleware 2023 - Proceedings of the 24th ACM/IFIP International Middleware Conference |
Place of Publication | New York |
Publisher | ACM |
Pages | 98–110 |
Number of pages | 13 |
ISBN (Electronic) | 9798400701771 |
ISBN (Print) | 979-8-4007-0177-1 |
DOIs | |
Publication status | Published - 2023 |
Event | Middleware '23: 24th International Middleware Conference - Bologna, Italy Duration: 11 Dec 2023 → 15 Dec 2023 Conference number: 24th |
Publication series
Name | Middleware 2023 - Proceedings of the 24th ACM/IFIP International Middleware Conference |
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Conference
Conference | Middleware '23 |
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Country/Territory | Italy |
City | Bologna |
Period | 11/12/23 → 15/12/23 |
Keywords
- Blockchain
- Mempool
- Accountability
- Transaction reordering