A COMPARATIVE ANALYSIS OF DIFFERENT FEATURE SET ON THE PERFORMANCE OF DIFFERENT ALGORITHMS IN PHISHING WEBSITE DETECTION

H. Musa, Bala Modi, Ismail Abdulkarim Adamu, Ali Ahmad Aminu, H. Adamu, Yahaya Ajiya
{"title":"A COMPARATIVE ANALYSIS OF DIFFERENT FEATURE SET ON THE PERFORMANCE OF DIFFERENT ALGORITHMS IN PHISHING WEBSITE DETECTION","authors":"H. Musa, Bala Modi, Ismail Abdulkarim Adamu, Ali Ahmad Aminu, H. Adamu, Yahaya Ajiya","doi":"10.5121/IJAIA.2019.10304","DOIUrl":null,"url":null,"abstract":"Reducing the risk pose by phishers and other cybercriminals in the cyber space requires a robust and automatic means of detecting phishing websites, since the culprits are constantly coming up with new techniques of achieving their goals almost on daily basis. Phishers are constantly evolving the methods they used for luring user to revealing their sensitive information. Many methods have been proposed in past for phishing detection. But the quest for better solution is still on. This research covers the development of phishing website model based on different algorithms with different set of features in order to investigate the most significant features in the dataset.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5121/IJAIA.2019.10304","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of artificial intelligence & applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJAIA.2019.10304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Reducing the risk pose by phishers and other cybercriminals in the cyber space requires a robust and automatic means of detecting phishing websites, since the culprits are constantly coming up with new techniques of achieving their goals almost on daily basis. Phishers are constantly evolving the methods they used for luring user to revealing their sensitive information. Many methods have been proposed in past for phishing detection. But the quest for better solution is still on. This research covers the development of phishing website model based on different algorithms with different set of features in order to investigate the most significant features in the dataset.
不同特征集的比较分析不同算法在钓鱼网站检测中的性能
降低网络钓鱼者和其他网络罪犯在网络空间中构成的风险需要一种强大而自动的检测网络钓鱼网站的方法,因为罪犯几乎每天都在不断想出实现目标的新技术。网络钓鱼者不断发展他们用来引诱用户泄露敏感信息的方法。过去已经提出了许多用于网络钓鱼检测的方法。但更好的解决方案仍在探索中。本研究涵盖了基于不同算法和不同特征集的钓鱼网站模型的开发,以研究数据集中最重要的特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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