【Author】
Drezewski, Rafal; Sepielak, Jan; Filipkowski, Wojciech
【Source】DIGITAL INVESTIGATION
【Abstract】Criminal analysis is a complex process involving information gathered from different sources, mainly of quantitative character, such as billings or bank account transactions, but also of qualitative character such as eyewitnesses' testimonies. Due to the massive nature of this information, operational or investigation activities can be vastly improved when supported by dedicated techniques and tools. The system supporting the police analyst in the process of detecting money laundering is presented in this paper. The main parts of the system are data importer and analyzing algorithms, such as transaction mining algorithm and frequent pattern mining algorithms. The results obtained with the use of these algorithms can be visualized, so that they can be easily explored by the police analyst. The transactions found can be treated as suspected operations. The frequent patterns found are mainly used to identify the roles of suspected entities. For the transaction mining algorithm a performance study is also presented. (C) 2012 Elsevier Ltd. All rights reserved.
【Keywords】Money laundering; Money transfer analysis; Clustering; Frequent patterns; Bank statement import
【摘要】刑事分析是一个复杂的过程，涉及从不同来源收集的信息，主要是数量特征，如账单或银行帐户交易，但也有定性特征，如目击者的证词。由于这些信息的大量性质，在专用技术和工具的支持下，操作或调查活动可以得到极大的改进。本文介绍了一种支持警务分析人员在侦查洗钱过程中工作的系统。系统的主要部分是数据导入和分析算法，如事务挖掘算法和频繁模式挖掘算法。使用这些算法得到的结果可以可视化，以便于警察分析人员进行探索。发现的事务可以作为可疑操作处理。发现的频繁模式主要用于识别可疑实体的角色。对事务挖掘算法进行了性能研究。(C) 2012爱思唯尔有限公司保留所有权利。
【关键词】洗钱;资金转移分析;聚类;频繁的模式;银行对账单导入
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