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基于交易时间衰减的以太坊恶意地址检测方法
网络安全与数据治理
梁飞1,石文君2,苏则燊3,张敏4
1.北京市公安局经济犯罪侦查总队;2.北京市公安局海淀分局; 3.华中科技大学;4.北京市公安局网络安全保卫总队
摘要: 提出Trans-TAN模型,用于以太坊上的交易流向图中关联恶意地址的检测任务,模型改进基于Transformer模型的自注意力机制,根据以太坊地址的交易特点并受到牛顿冷却定理的启发,引入随时间交易的时间间隔衰减因素,同时融合以太坊地址间的相似度因素和交易金额因素。基于以上三方面,通过牛顿冷却定理的常微分方程解形式构建的地址关联矩阵,从而改进原有的自注意力矩阵。实验证明,Trans-TAN模型能够有效捕捉以太坊交易流向图过程中恶意节点地址的特征,在测试集中精准率 (Precision)、召回率(Recall)和F1指标优于传统的检测模型。
中图分类号:TP311.13;TP309;TP183文献标识码:ADOI:10.19358/j.issn.2097-1788.2024.07.005
引用格式:梁飞,石文君,苏则燊,等.基于交易时间衰减的以太坊恶意地址检测方法[J].网络安全与数据治理,2024,43(7):26-31.
Ethereum malicious address detection method based on transaction time decay
Liang Fei1,Shi Wenjun2,Su Zeshen3 ,Zhang Min4
1. Economic Crime Investigation Brigade of Beijing Municipal Public Security Bureau; 2. Haidian Branch of Beijing Municipal Public Security Bureau; 3. Huazhong University of Science and Technology; 4. Beijing Municipal Public Security Bureau Network Security Corps
Abstract: This article proposes the Trans-TAN model for detecting malicious addresses associated with transaction flow graphs on Ethereum. The model improves the self attention mechanism based on the Transformer model. Inspired by Newton′s cooling theorem and based on the transaction characteristics of Ethereum addresses, the Trans-TAN model introduces the time decay factor of transaction intervals over time. At the same time, it integrates the similarity factor between Ethereum addresses and the transaction amount factor. Based on the above three factors, the address association matrix is constructed in the form of a solution to the ordinary differential equation of Newton′s cooling theorem, thereby improving the original self attention matrix. Experimental results show that the Trans-TAN model can effectively capture the characteristics of malicious node addresses in the Ethereum transaction flow graph process, and its accuracy in the test set (Pre) is improved. The precision, recall, and F1 metrics are superior to traditional detection models.
Key words : Ethereum account; Newton′s cooling theorem; time interval decay; self attention mechanism

引言

近年来利用虚拟货币为媒介的犯罪日趋猖獗,传统的网络赌博、网络黑灰产、洗钱[1]等正在借助虚拟货币匿名性和去中心化的特点实现支付结算。同时利用虚拟货币从事网络赌博、诈骗、传销类、洗钱类、黑灰产类的案件呈高发态势,例如在2023年底北京市经侦总队破获了北京市首例利用虚拟货币从事非法换汇案件,嫌疑人利用虚拟货币为境内人员换汇金额高达10亿元,严重扰乱金融秩序,因此建立以技术手段为基础从而阻断使用虚拟货币沦为犯罪工具显得迫在眉睫。


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作者信息:

梁飞1,石文君2,苏则燊3,张敏4

(1.北京市公安局经济犯罪侦查总队,北京100062;

2.北京市公安局海淀分局,北京100086;

3.华中科技大学,湖北武汉430074;

4.北京市公安局网络安全保卫总队,北京100081)


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