A Geth-based real-time detection system for sandwich attacks in Ethereum

IF 1.7 3区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Dongze Li, Kejia Zhang, Lei Wang, Gang Du
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Abstract

With the rapid development of the Ethereum ecosystem and the increasing applications of decentralized finance (DeFi), the security research of smart contracts and blockchain transactions has attracted more and more attention. In particular, front-running attacks on the Ethereum platform have become a major security concern. These attack strategies exploit the transparency and certainty of the blockchain, enabling attackers to gain unfair economic benefits by manipulating the transaction order. This study proposes a sandwich attack detection system integrated into the go-Ethereum client (Geth). This system, by analyzing transaction data streams, effectively detects and defends against front-running and sandwich attacks. It achieves real-time analysis of transactions within blocks, quickly and effectively identifying abnormal patterns and potential attack behaviors. The system has been optimized for performance, with an average processing time of 0.442 s per block and an accuracy rate of 83%. Response time for real-time detection new blocks is within 5 s, with the majority occurring between 1 and 2 s, which is considered acceptable. Research findings indicate that as a part of the go-Ethereum client, this detection system helps enhance the security of the Ethereum blockchain, contributing to the protection of DeFi users’ private funds and the safety of smart contracts. The primary contribution of this study lies in offering an efficient blockchain transaction monitoring system, capable of accurately detecting sandwich attack transactions within blocks while maintaining normal operation speeds as a full node.

Abstract Image

基于 Geth 的以太坊三明治攻击实时检测系统
随着以太坊生态系统的快速发展和去中心化金融(DeFi)应用的不断增加,智能合约和区块链交易的安全研究引起了越来越多的关注。特别是,以太坊平台上的前置运行攻击已成为一个主要的安全问题。这些攻击策略利用了区块链的透明性和确定性,使攻击者能够通过操纵交易顺序获得不公平的经济利益。本研究提出了一种集成到 go-Ethereum 客户端(Geth)中的三明治攻击检测系统。该系统通过分析交易数据流,有效检测和防御前置运行攻击和三明治攻击。它能对区块内的交易进行实时分析,快速有效地识别异常模式和潜在攻击行为。该系统对性能进行了优化,每个区块的平均处理时间为 0.442 秒,准确率高达 83%。实时检测新数据块的响应时间在 5 秒以内,大部分在 1 到 2 秒之间,这被认为是可以接受的。研究结果表明,作为 go-Ethereum 客户端的一部分,该检测系统有助于增强以太坊区块链的安全性,有助于保护 DeFi 用户的私人资金和智能合约的安全。本研究的主要贡献在于提供了一个高效的区块链交易监控系统,能够准确检测区块内的夹层攻击交易,同时保持作为完整节点的正常运行速度。
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来源期刊
Information Retrieval Journal
Information Retrieval Journal 工程技术-计算机:信息系统
CiteScore
6.20
自引率
0.00%
发文量
17
审稿时长
13.5 months
期刊介绍: The journal provides an international forum for the publication of theory, algorithms, analysis and experiments across the broad area of information retrieval. Topics of interest include search, indexing, analysis, and evaluation for applications such as the web, social and streaming media, recommender systems, and text archives. This includes research on human factors in search, bridging artificial intelligence and information retrieval, and domain-specific search applications.
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