文章基本信息

标题：IDENTIFICATION OF FRAUD ATTRIBUTES FOR DETECTING FRAUD BASED ONLINE SALES TRANSACTION
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作者：Solichul Huda ; Aripin ; Mohammad Farid Naufal 等
期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2021
卷号：12
期号：5
页码：1409-1424
DOI：10.21817/indjcse/2021/v12i5/211205083
语种：English
出版社：Engg Journals Publications
摘要：Fraud can occur in transactions or in business processes. Process-mining approach can be used to detect fraud in business processes. Methods of fraud detection based on process mining have been proposed in several previous studies. The methods used included throughput time analysis, wrong pattern analysis and decision analysis. However, errors still occur in identifying fraud in online sales transactions. Thus, we propose the distant events method and distant events method for analysis of the distance between activities and analysis of the number of activities to identify any fraud issue in online sales transaction process. We analyze the activities carried out by consumers starting from the selection of the good, ordering the good, and the payment of the good activities. Then, the methods analyzes the time gap between activities and the total number of activities for each sales transaction. Furthermore, we did conformance on the results of the analysis with the Standard Operating Procedure (SOP). The violation of the SOP in a sales transaction processes are called the distant events and added event attributes. Prior to the delivery of the purchased good, this fraud detection system will determine these identified attributes of fraud as fraud or not. If the purchase process is identified as fraud, the delivery process of the good bought is canceled. This study proves that by using analysis on the activities distance and analysis on the added activities in online sales transactions, it can reduce false negatives and also increase the accuracy by 0.8 than that by previous methods.
关键词：Fraud Detection;Process Model;Fraud Attribute;Process Mining;Online Sales