Reasoning method for predicting crime partner by using intimacy network of bank accounts

Fang LYU; Haibo LU; Wei WANG; Junheng HUANG; Bailing WANG

doi:10.11959/j.issn.2096-109x.2019062

您当前的位置：

首页 >

文章列表页 >

Reasoning method for predicting crime partner by using intimacy network of bank accounts

Papers | 更新时间：2024-06-03

- Reasoning method for predicting crime partner by using intimacy network of bank accounts
- Chinese Journal of Network and Information Security Vol. 5, Issue 6, Pages: 95-104(2019)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2019062
  CLC： TP391.4
- Online First：2019-12，
  
  Published：15 December 2019
- 稿件说明：
移动端阅览
Fang LYU, Haibo LU, Wei WANG, et al. Reasoning method for predicting crime partner by using intimacy network of bank accounts[J]. Chinese Journal of Network and Information Security, 2019, 5(6): 95-104.
DOI：

Fang LYU, Haibo LU, Wei WANG, et al. Reasoning method for predicting crime partner by using intimacy network of bank accounts[J]. Chinese Journal of Network and Information Security, 2019, 5(6): 95-104. DOI： 10.11959/j.issn.2096-109x.2019062.

摘要

近年来，针对涉众型非法金融活动在资金交易规律的研究引起了研究者的高度关注。为解决利用银行交易数据进行异常账户犯罪团伙主动发现的问题，提出一种基于银行账户非对称亲密度网络的团伙预测方法。首先，建立银行账户交易通用网络模型，将时序交易数据嵌入网络结构中。然后，利用节点的直接和间接交易关系信息，提出一种账户非对称亲密度计算方法。最终，利用节点在亲密度网络上的非对称交互信息，得到节点的异常倾向性指标。在包含传销团伙的真实数据上的实验结果表明，基于亲密度网络的团伙预测方法能有效发现潜在传销人员。

Abstract

In recent years

research on the law of capital transactions in the case of stakeholder-type illegal financial activities has attracted the attention of researchers.In order to solve the problem of using the bank transaction data to actively discover the abnormal account criminal crime partners

a crime partner prediction method based on the asymmetric intimacy network of the bank accounts was proposed.Firstly

a general network model for bank account transactions was established to embed time-series transaction data into the network structure.Then

using the direct and indirect transaction relationship information of the node

an account asymmetric intimacy calculation method was proposed.Finally

using the asymmetric interaction information of the nodes on the intimate network

the abnormal tendency index of the nodes is obtained.The experimental results on the actual data of the multi-level marketing group show that the crime partner prediction method based on the intimacy network can effectively find potential pyramid shelling members.

关键词

Keywords

references

陈鹏 , 袁宏永 . 犯罪组织结构的社会网络分析 [J ] . 清华大学学报(自然科学版) , 2011 , 51 ( 8 ): 1097 - 1101 .

CHEN P , YUAN H Y . Social network analysis of crime organization structures [J ] . Journal of Tsinghua University (Science and Technology) , 2011 , 51 ( 8 ): 1097 - 1101 .

LIU J X . The research on detecting community structure of complex networks and its application in financial Networks [D ] . Lanzhou:Lanzhou University of Technology , 2013 .

韩华 , 吴翎燕 , 宋宁宁 . 基于随机矩阵的金融网络模型 [J ] . 物理学报 , 2014 , 63 ( 13 ): 431 - 440 .

HAN H , WU L Y , SONG N N . Financial networks model based on random matrix [J ] . Acta Physica Sinica , 2014 , 63 ( 13 ): 431 - 440 ,2014.

李琼婕 , 薛耀文 . 最小费用最大流维度拓展及其在反洗钱中的应用研究 [J ] . 山西师范大学学报（自然科学版） , 2014 , 28 ( 1 ): 28 - 32 .

LI Q J , XUE Y W . Dimension-expansion of minimum cost and maximum flow theory and its application research in anti-money laundering [J ] . Journal of Shanxi Normal University (Science and Technology) , 2014 , 28 ( 1 ): 28 - 32 .

ADAMIC L A , ADAR E . Friends and neighbors on the Web [J ] . Social Networks , 2003 , 25 ( 3 ): 211 - 230 .

WU Z H , LIN Y F . Link prediction with node clustering coefficient [J ] . Physica A:Statistical Mechanics and Its Applications , 2016 , 452 : 1 - 8 .

ZHOU T , LYU L Y , ZHANG Y C . Predicting missing links via local information [J ] . The European Physical Journal B , 2009 , 71 ( 4 ): 623 - 630 .

LEICHT E A , HOLME P , NEWMAN M E J . Vertex similarity in networks [J ] . Physical Review E Statistical Nonlinear and Soft Matter Physics , 2006 , 73 ( 2 ): 1 - 10 .

ZHU X Z , TIAN H , CAI S M . Predicting missing links via effective paths [J ] . Physica A:Statistical Mechanics and Its Applications , 2014 , 413 ( 11 ): 515 - 522 .

PEROZZI B , RAMI A R , SKIENA S . DeepWalk:anline learning of social representations [C ] // ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’14) . 2014 : 701 - 710 .

TANG J , QU M , WANG M , et al . LINE:large-scale information network embedding [C ] // International Conference on World Wide Web (WWW’15) . 2015 : 1067 - 1077 .

WANG D X , CUI P , ZHU W W . Structural deep network embedding [C ] // ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’16) . 2016 : 1225 - 1234 .

DONNAT C , MARINKA Z , HALLAC D , et al . Learning structural node embeddings via diffusion wavelets [C ] // ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD’18) . 2018 .

SUN Y , TAN W N , LI L X , et al . A new method to identify collaborative partners in social service provider networks [J ] . Information Systems Frontiers , 2016 , 18 ( 3 ).

CHEN H , CHUNG W , XU J J , et al . Crime data mining:a general framework and some examples [J ] . Computer , 2004 , 37 ( 4 ): 50 - 56 .

杨莉莉 , 杨永川 . 基于社会网络的犯罪组织关系挖掘 [J ] . 计算机工程 , 2009 , 35 ( 15 ): 91 - 93 .

YANG L L , YANG Y C . Crime organization relation mining based on social network [J ] . Computer Engineering , 2009 , 35 ( 15 ): 91 - 93 .

高建强 , 谭剑 , 崔永发 . 一种基于通讯痕迹的社会网络团伙分析模型 [J ] . 计算机应用与软件 , 2012 , 29 ( 3 ): 206 - 208 .

GAO J Q , TAN J , CUI Y F . One social network clique analysis model based on communication trace [J ] . Computer Applications and Software , 2012 , 29 ( 3 ): 206 - 208 .

李万彪 , 余志 , 龚峻峰 , 等 . 基于关系数据模型的犯罪网络挖掘研究 [J ] . 中山大学学报（自然科学版） , 2014 , 53 ( 5 ): 1 - 7 .

LI W B , YU Z , GONG J F , et al . An approach of crime network analysis based on association data model [J ] . Acta Scientiarum Anturalium Universitatis Sunyatseni , 2014 , 53 ( 5 ): 1 - 7 .

唐德权 , 史伟奇 , 凌志刚 . 有组织犯罪集团挖掘算法 [J ] . 计算机系统应用 , 2015 , 24 ( 9 ): 196 - 200 .

TANG D Q , SHI W Q , LING Z G . Algorithm for mining organized crime [J ] . Computer Systems ＆ Applications , 2015 , 24 ( 9 ): 196 - 200 .

Views

342

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Analyzing the complex properties of bank account transaction network

Related Author

Fang LYU

Xinlin ZHANG

Wei WANG

Junheng HUANG

Bailing WANG

Related Institution

No data

⁰