Design and implementation of a real-time detection system for multi-token sandwich attacks in Ethereum based on Geth client

The Ethereum platform is booming with growing richness and variety in decentralized finance (DeFi) products. However, this progress comes with sophisticated threats, such as sandwich attacks, where attackers exploit the openness and certainty of blockchain technology to manipulate market prices and secure illegal financial rewards through a strategically planned series of transactions. The existing sandwich attack detection methods are ineffective at detecting multi-token transactions and fail to identify multi-token sandwich attacks. To tackle this challenge, this study improves the original detector’s algorithm to identify both traditional single-token and multi-token sandwich attacks. The enhanced system is not only responsive and accurate but also capable of detecting and alerting potential multi-token sandwich attacks. It has been successfully integrated with the go-Ethereum client (Geth). The system is performance-optimized with an average processing time of 0.81 seconds per block and an accuracy rate of 96.17%. The response time for detecting new blocks in real-time is usually no more than 4 seconds, with most between 2 and 3 seconds, which meets practical application requirements. By carefully analyzing the transaction data flow, this system is not only able to identify the traditional front-running attack and sandwich attack, but also extends to multi-currency complex attack strategies. The core innovation lies in the system’s ability to accurately detect and provide early warnings of multi-token sandwich attacks through real-time analysis of in-block transactions, all while maintaining the overall operational efficiency of the node.

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Publication Details

Journal
Discover Computing
Published
2025-08-25
DOI
https://doi.org/10.1007/s10791-025-09694-z
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

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article

Design and implementation of a real-time detection system for multi-token sandwich attacks in Ethereum based on Geth client

Jinyu Bai, Gang Du, Dongze Li, Zhenxuan Jiang
Discover Computing
Blockchain Technology Applications and Security
article

Design and implementation of a real-time detection system for multi-token sandwich attacks in Ethereum based on Geth client

Jinyu Bai, Gang Du, Dongze Li, Zhenxuan Jiang
article en

Abstract

The Ethereum platform is booming with growing richness and variety in decentralized finance (DeFi) products. However, this progress comes with sophisticated threats, such as sandwich attacks, where attackers exploit the openness and certainty of blockchain technology to manipulate market prices and secure illegal financial rewards through a strategically planned series of transactions. The existing sandwich attack detection methods are ineffective at detecting multi-token transactions and fail to identify multi-token sandwich attacks. To tackle this challenge, this study improves the original detector’s algorithm to identify both traditional single-token and multi-token sandwich attacks. The enhanced system is not only responsive and accurate but also capable of detecting and alerting potential multi-token sandwich attacks. It has been successfully integrated with the go-Ethereum client (Geth). The system is performance-optimized with an average processing time of 0.81 seconds per block and an accuracy rate of 96.17%. The response time for detecting new blocks in real-time is usually no more than 4 seconds, with most between 2 and 3 seconds, which meets practical application requirements. By carefully analyzing the transaction data flow, this system is not only able to identify the traditional front-running attack and sandwich attack, but also extends to multi-currency complex attack strategies. The core innovation lies in the system’s ability to accurately detect and provide early warnings of multi-token sandwich attacks through real-time analysis of in-block transactions, all while maintaining the overall operational efficiency of the node.

Discover ComputingVol. 28(1)
Heilongjiang University (CN)
Heilongjiang University, National Natural Science Foundation of China, Guizhou University, Natural Science Foundation of Heilongjiang Province
Openalex Percentile: Top 67%
Blockchain Technology Applications and Security
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