基于数据挖掘的身份犯罪侦查

Sharmistha Dutta, Ankit Gupta, Neetu Narayan
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引用次数: 14

摘要

身份犯罪是指伪装身份,窃取与当事人身份有关的机密信息的犯罪。本文主要研究与信用卡申请有关的身份犯罪,这类犯罪在当今非常普遍,甚至代价高昂。针对现有的消除身份盗窃的非数据挖掘技术存在的缺陷,提出了一种新的数据挖掘防御层。这个新层利用两种算法——公共检测和峰值检测来检测应用程序中的欺诈行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identity Crime Detection Using Data Mining
Identity Crime is considered as crimes which involve masquerading one's identity and steal confidential information with respect to the concerned person's identity. This paper mainly deals with identity crime related to credit card application, which nowadays is quite prevalent and costly even. The existing non data-mining techniques for eliminating identity theft have some flaws and to combat them a new data-mining layer of defence has been proposed. This novel layer makes use of two algorithms-Communal Detection and Spike Detection for detecting frauds in applications.
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