电子商业环境的欺诈预防框架:自动隔离网络钓鱼企图

Nazeeh Ghatasheh
{"title":"电子商业环境的欺诈预防框架:自动隔离网络钓鱼企图","authors":"Nazeeh Ghatasheh","doi":"10.1109/CCC.2016.17","DOIUrl":null,"url":null,"abstract":"In the era of digital economy and high penetration rate of technology, cybercrime is taking over a great span of the cyberworld. Novice to experienced users are subject to being victims to cyber criminals. Phishing attempts lead to critical issues and risks for online users, and for companies as well. This research proposes a framework for fraud prevention by enabling the automatic detection of malicious websites. The applicability of the framework is validated by various types of experiments. The experiments tries to model phishing websites using various algorithms and approaches, including hybrid approaches. It is apparent that the performance of Random Forest Trees algorithm overperformed several other algorithms. Accordingly, the framework is proved to be useful in the segregation of malicious online content and phishing attempts. In addition the results call for more investigation and improvement in fraud prevention approaches.","PeriodicalId":120509,"journal":{"name":"2016 Cybersecurity and Cyberforensics Conference (CCC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fraud Prevention Framework for Electronic Business Environments: Automatic Segregation of Online Phishing Attempts\",\"authors\":\"Nazeeh Ghatasheh\",\"doi\":\"10.1109/CCC.2016.17\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the era of digital economy and high penetration rate of technology, cybercrime is taking over a great span of the cyberworld. Novice to experienced users are subject to being victims to cyber criminals. Phishing attempts lead to critical issues and risks for online users, and for companies as well. This research proposes a framework for fraud prevention by enabling the automatic detection of malicious websites. The applicability of the framework is validated by various types of experiments. The experiments tries to model phishing websites using various algorithms and approaches, including hybrid approaches. It is apparent that the performance of Random Forest Trees algorithm overperformed several other algorithms. Accordingly, the framework is proved to be useful in the segregation of malicious online content and phishing attempts. In addition the results call for more investigation and improvement in fraud prevention approaches.\",\"PeriodicalId\":120509,\"journal\":{\"name\":\"2016 Cybersecurity and Cyberforensics Conference (CCC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Cybersecurity and Cyberforensics Conference (CCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCC.2016.17\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Cybersecurity and Cyberforensics Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCC.2016.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在数字经济和高技术普及率的时代,网络犯罪正在网络世界中大行其道。从新手到资深用户都有可能成为网络罪犯的受害者。网络钓鱼企图给网络用户和公司带来了严重的问题和风险。本研究提出了一个通过自动检测恶意网站来预防欺诈的框架。各种类型的实验验证了该框架的适用性。实验尝试使用各种算法和方法(包括混合方法)对钓鱼网站进行建模。显然,随机森林树算法的性能优于其他几种算法。因此,该框架被证明在隔离恶意在线内容和网络钓鱼尝试方面非常有用。此外,研究结果还要求对欺诈预防方法进行更多的调查和改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fraud Prevention Framework for Electronic Business Environments: Automatic Segregation of Online Phishing Attempts
In the era of digital economy and high penetration rate of technology, cybercrime is taking over a great span of the cyberworld. Novice to experienced users are subject to being victims to cyber criminals. Phishing attempts lead to critical issues and risks for online users, and for companies as well. This research proposes a framework for fraud prevention by enabling the automatic detection of malicious websites. The applicability of the framework is validated by various types of experiments. The experiments tries to model phishing websites using various algorithms and approaches, including hybrid approaches. It is apparent that the performance of Random Forest Trees algorithm overperformed several other algorithms. Accordingly, the framework is proved to be useful in the segregation of malicious online content and phishing attempts. In addition the results call for more investigation and improvement in fraud prevention approaches.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信