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基于信息熵的金融网络洗钱社区发现新算法

2017-09-08吕林涛袁琴琴吕晖李婉荣

现代电子技术 2017年17期

吕林涛+袁琴琴+吕晖+李婉荣

摘 要: 针对洗钱交易的大数据大额可疑特征和量化特点,基于凝聚和优化指标的思想,提出一种ML?CDBIE算法。该算法根据节点信息熵的相似性和社区信息熵的稳定性进行洗钱社区发现。根据增加节点后社区熵的变化是否剧烈可以判断节点的划分是否正确,是否属于社区的成员,从而实现洗钱社区的发现。实验结果表明,该算法不仅具有洗钱账户识别率高和良好的社区结构,而且为金融网络洗钱社区发现提供了一种新途径。

关键词: 金融网络; 洗钱交易; 信息熵; 社区发现; 社区划分

中图分类号: TN911.1?34; TP393 文献标识码: A 文章编号: 1004?373X(2017)17?0131?04

An information entropy based new money laundering community

discovery algorithm of financial network

L? Lintao1, YUAN Qinqin1, L? Hui2, LI Wanrong3

(1. Department of Information Engineering, Xijing University, Xian 710123, China;

2. College of Civil Engineering, Chongqing University, Chongqing 400044, China;

3. College of Computer Science and Engineering, Xian University of Technology, Xian 710048, China)

Abstract: According to the large quantity and suspicious characteristic and quantitative features of money laundering transaction, a money laundering community discovery algorithm based on information entropy (ML?CDBIE) is proposed according to the thoughts of aggregation and indicator optimization. The characteristic of the algorithm is to discover money laundering community according to the similarity of nodes information entropy and stability of community information entropy. According to the dramatic change of the community entropy after nodes addition, it can determine whether the nodes division is correct, or belongs to the community, which can discover the money laundering community. The experimental results show that the algorithm has high recognition rate and perfect community structure of money laundering account, and also provides a new way to discover the money laundering community of financial network.

Keywords: financial network; money laundering transaction; information entropy; community discovery; community division

0 引 言

隨着金融系统的全球化、信息化和网络化发展,使得资本在世界范围内以更快更便捷的方式流动,但是如何有效防范金融网络中的洗钱犯罪行为已成为当前人们关注的热点。

目前,社区发现技术不仅应用于网络结构、分析网络个体间关系,而且也是解决挖掘网络中隐藏有价值的大数据的一种有效途径。因此,为了有效获取复杂金融网络的洗钱社区,本文基于信息熵的社区发现技术,根据金融网络中的交易结构及洗钱交易的大额和可疑特征,建立了将交易账户映射为网络中的节点,账户间的交易关系映射为网络中边的数学模型,并针对洗钱交易的大数据大额可疑特征和量化等特点,提出一种基于信息熵的洗钱社区发现算法,通过应用后表明,该方法不仅解决了金融网络中节点社区快速有效的划分,而且也能依据可疑交易特征发现洗钱社区,从而为金融安全交易提供了有力保障。……

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