以太坊钓鱼诈骗检测技术综述

蔡召; 荆涛; 任爽

doi:10.11959/j.issn.2096-109x.2023018

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以太坊钓鱼诈骗检测技术综述

综述 | 更新时间：2024-06-03

- 以太坊钓鱼诈骗检测技术综述
- Survey on Ethereum phishing detection technology
- 网络与信息安全学报 2023年9卷第2期页码：21-32
- 作者机构：
- 作者简介：
  
  [ "蔡召（1998- ），男，安徽宿州人，北京交通大学硕士生，主要研究方向为区块链交易网络、网络表示学习" ]
  [ "荆涛（1969- ），男，吉林吉林人，北京交通大学教授、博士生导师，主要研究方向为网络与信息安全、人工智能" ]
  [ "任爽（1981- ），男，吉林长春人，北京交通大学副教授、博士生导师，主要研究方向为区块链、人工智能" ]
- 基金信息：
  
  国家自然科学基金;The National Natural Science Foundation of China(62072025)
- DOI：10.11959/j.issn.2096-109x.2023018
  中图分类号： TP393
- 网络首发：2023-04，
  
  纸质出版：2023-04-25
- 稿件说明：
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蔡召, 荆涛, 任爽. 以太坊钓鱼诈骗检测技术综述[J]. 网络与信息安全学报, 2023,9(2):21-32.

Zhao CAI, Tao JING, Shuang REN. Survey on Ethereum phishing detection technology[J]. Chinese Journal of Network and Information Security, 2023, 9(2): 21-32.
蔡召, 荆涛, 任爽. 以太坊钓鱼诈骗检测技术综述[J]. 网络与信息安全学报, 2023,9(2):21-32. DOI： 10.11959/j.issn.2096-109x.2023018.

Zhao CAI, Tao JING, Shuang REN. Survey on Ethereum phishing detection technology[J]. Chinese Journal of Network and Information Security, 2023, 9(2): 21-32. DOI： 10.11959/j.issn.2096-109x.2023018.

摘要

随着区块链技术的广泛应用，网络钓鱼诈骗成为区块链平台上的一大威胁。由于区块链交易具有不可逆性、匿名性和难以篡改性等特点，网络钓鱼攻击往往具有高度的欺骗性和隐蔽性，给用户和企业带来了巨大损失。其中，以太坊平台因其智能合约功能而备受瞩目，并吸引了众多“加密货币”投资者。然而，这种广泛流行也导致了一些不法分子的涌入，滋生了许多网络犯罪行为。其中，钓鱼诈骗是以太坊平台上主要的诈骗形式之一。针对这种情况，以太坊网络钓鱼检测技术应运而生，研究者在该领域取得了众多成果，但对这些研究成果的系统分析和总结相对较少。深入分析了以太坊上网络钓鱼诈骗的现状，对已有的钓鱼诈骗检测数据集和评价指标进行了全面总结。在此基础上，进一步综述了以太坊钓鱼诈骗检测的方法，包括基于交易信息、基于图嵌入和基于图神经网络的方法。其中，基于交易信息的方法是最为常见的，通过分析交易数据的输入地址、输出地址和数额等信息，来判断交易是否存在异常。基于图嵌入和基于图神经网络的方法则更加注重对整个交易网络的分析，通过构建图结构来分析节点之间的关系，从而更加精准地识别钓鱼攻击。对比分析了各方法的优缺点，说明了各方法的适用范围和局限性。进一步指出了以太坊钓鱼诈骗检测面临的挑战，并展望了以太坊钓鱼诈骗检测未来的研究趋势。

Abstract

With the widespread application of blockchain technology

phishing scams have become a major threat to blockchain platforms.Due to the irreversibility

anonymity

and tamper-proof nature of blockchain transactions

phishing attacks often have a high degree of deception and concealment

causing significant losses to both users and businesses.Ethereum platform

with its smart contract functionality

has attracted many crypto currency investors.However

this widespread popularity has also attracted an influx of criminals

leading to the rise of cybercrime activities.Among them

phishing scams are one of the main forms of fraud on the Ethereum platform.To tackle this issue

researchers have developed Ethereum network phishing identification technology

achieving significant progress in this field.However

there has been relatively little systematic analysis and summary of these research results.The current state of phishing fraud on the Ethereum network was analyzed.Moreover

a comprehensive summary of existing phishing detection datasets and evaluation metrics were provided.On this basis

methods for detecting phishing on Ethereum were reviewed

including those based on transaction information

graph embedding and graph neural networks.Transaction information-based methods are the most common

analyzing information such as input and output addresses and amounts in transaction data to determine whether a transaction is abnormal.Methods based on graph embedding and graph neural networks place more emphasis on analyzing the entire transaction network

constructing a graph structure to analyze the relationships between nodes

and more accurately identifying phishing attacks.In addition

a comparative analysis of the advantages and disadvantages of various methods was conducted

explaining the applicability and limitations of each method.Finally

the challenges facing Ethereum phishing detection were pointed out

and the future research trends for Ethereum phishing detection were predicted.

关键词

Keywords

references

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