在安装流动应用程序时，欺诈者指纹的形成方法

2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) Pub Date : 2019-09-01 DOI:10.1109/IDAACS.2019.8924369

T. Polhul, A. Yarovyi

{"title":"在安装流动应用程序时，欺诈者指纹的形成方法","authors":"T. Polhul, A. Yarovyi","doi":"10.1109/IDAACS.2019.8924369","DOIUrl":null,"url":null,"abstract":"This study aimed to develop a method of fraudster fingerprint formation during mobile application installations, based on a fuzzy model for fraudster fingerprint formation and algorithms of its use for fraudster fingerprint formation. This method allows determining the reason of labeling user by a particular class during fraud detection. The use of the developed method in fraud detection tasks makes it possible to correctly identify 99.56% of users in general and 80.43% of correctly determined fraudsters in particular and speed up the fraud detection process.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method of Fraudster Fingerprint Formation During Mobile Application Installations\",\"authors\":\"T. Polhul, A. Yarovyi\",\"doi\":\"10.1109/IDAACS.2019.8924369\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aimed to develop a method of fraudster fingerprint formation during mobile application installations, based on a fuzzy model for fraudster fingerprint formation and algorithms of its use for fraudster fingerprint formation. This method allows determining the reason of labeling user by a particular class during fraud detection. The use of the developed method in fraud detection tasks makes it possible to correctly identify 99.56% of users in general and 80.43% of correctly determined fraudsters in particular and speed up the fraud detection process.\",\"PeriodicalId\":415006,\"journal\":{\"name\":\"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)\",\"volume\":\"254 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAACS.2019.8924369\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2019.8924369","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本研究旨在基于欺诈者指纹形成的模糊模型及其用于欺诈者指纹形成的算法，开发一种在移动应用程序安装过程中欺诈者指纹形成的方法。该方法允许在欺诈检测期间确定由特定类标记用户的原因。在欺诈检测任务中使用所开发的方法，可以正确识别99.56%的一般用户和80.43%正确确定的特定欺诈者，并加快欺诈检测过程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Method of Fraudster Fingerprint Formation During Mobile Application Installations

This study aimed to develop a method of fraudster fingerprint formation during mobile application installations, based on a fuzzy model for fraudster fingerprint formation and algorithms of its use for fraudster fingerprint formation. This method allows determining the reason of labeling user by a particular class during fraud detection. The use of the developed method in fraud detection tasks makes it possible to correctly identify 99.56% of users in general and 80.43% of correctly determined fraudsters in particular and speed up the fraud detection process.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)

自引率

0.00%

发文量