网络钓鱼:使用丢弃的电子邮件地址调查网络钓鱼集群

Shams Zawoad, A. Dutta, A. Sprague, Ragib Hasan, Jason Britt, Gary Warner
{"title":"网络钓鱼:使用丢弃的电子邮件地址调查网络钓鱼集群","authors":"Shams Zawoad, A. Dutta, A. Sprague, Ragib Hasan, Jason Britt, Gary Warner","doi":"10.1109/ECRS.2013.6805777","DOIUrl":null,"url":null,"abstract":"The most common approach to collect users' secret credentials from phishing websites is to email the credentials to criminals' email addresses which we call drop email addresses. We propose a clustering algorithm, which is based on the assumption that if there is a common drop email address found in the phishing kits from two different phishing websites, then these two websites are directly related. Based on obfuscated and plain-text drop email addresses, we produce two types of clusters: one is called phishing kit creator cluster and another is kit user cluster. Clustering related phishing websites using our proposed approach will allow phishing investigators to focus their investigative efforts on important phishing attacks rather than random attacks. For example, in January 2013, 1475 phishing websites are hosted by only 317 groups of phishers (who we will call kit users). Our scheme will thus help investigators to narrow investigation to pervasive phishing criminals. By analyzing the clusters generated using our clustering approach, we can determine the strongest and most pervasive phishers, and phishing kit creators, relationships between phishing kit creators and phishing kit users, and the most dominant phisher of one group. These findings have real-life implication in phishing investigation paradigm.","PeriodicalId":110678,"journal":{"name":"2013 APWG eCrime Researchers Summit","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Phish-Net: Investigating phish clusters using drop email addresses\",\"authors\":\"Shams Zawoad, A. Dutta, A. Sprague, Ragib Hasan, Jason Britt, Gary Warner\",\"doi\":\"10.1109/ECRS.2013.6805777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The most common approach to collect users' secret credentials from phishing websites is to email the credentials to criminals' email addresses which we call drop email addresses. We propose a clustering algorithm, which is based on the assumption that if there is a common drop email address found in the phishing kits from two different phishing websites, then these two websites are directly related. Based on obfuscated and plain-text drop email addresses, we produce two types of clusters: one is called phishing kit creator cluster and another is kit user cluster. Clustering related phishing websites using our proposed approach will allow phishing investigators to focus their investigative efforts on important phishing attacks rather than random attacks. For example, in January 2013, 1475 phishing websites are hosted by only 317 groups of phishers (who we will call kit users). Our scheme will thus help investigators to narrow investigation to pervasive phishing criminals. By analyzing the clusters generated using our clustering approach, we can determine the strongest and most pervasive phishers, and phishing kit creators, relationships between phishing kit creators and phishing kit users, and the most dominant phisher of one group. These findings have real-life implication in phishing investigation paradigm.\",\"PeriodicalId\":110678,\"journal\":{\"name\":\"2013 APWG eCrime Researchers Summit\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 APWG eCrime Researchers Summit\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECRS.2013.6805777\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 APWG eCrime Researchers Summit","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECRS.2013.6805777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13

摘要

从钓鱼网站收集用户秘密凭证的最常见方法是将凭证通过电子邮件发送到犯罪分子的电子邮件地址,我们称之为删除电子邮件地址。我们提出了一种聚类算法,该算法基于这样的假设:如果在来自两个不同的网络钓鱼网站的网络钓鱼工具包中发现了一个共同的drop电子邮件地址,那么这两个网站就直接相关。基于模糊和纯文本丢弃的电子邮件地址,我们产生了两种类型的集群:一种称为钓鱼工具包创建者集群,另一种称为工具包用户集群。使用我们提出的方法聚类相关的网络钓鱼网站将允许网络钓鱼调查人员将他们的调查工作集中在重要的网络钓鱼攻击上,而不是随机攻击上。例如,2013年1月,1475个网络钓鱼网站由317个网络钓鱼组织(我们称之为工具包用户)托管。因此,我们的方案将帮助调查人员将调查范围缩小到无处不在的网络钓鱼罪犯。通过分析使用我们的聚类方法生成的聚类,我们可以确定最强和最普遍的网络钓鱼者、网络钓鱼工具包创建者、网络钓鱼工具包创建者和网络钓鱼工具包用户之间的关系,以及一组中最主要的网络钓鱼者。这些发现对网络钓鱼调查范式具有现实意义。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Phish-Net: Investigating phish clusters using drop email addresses
The most common approach to collect users' secret credentials from phishing websites is to email the credentials to criminals' email addresses which we call drop email addresses. We propose a clustering algorithm, which is based on the assumption that if there is a common drop email address found in the phishing kits from two different phishing websites, then these two websites are directly related. Based on obfuscated and plain-text drop email addresses, we produce two types of clusters: one is called phishing kit creator cluster and another is kit user cluster. Clustering related phishing websites using our proposed approach will allow phishing investigators to focus their investigative efforts on important phishing attacks rather than random attacks. For example, in January 2013, 1475 phishing websites are hosted by only 317 groups of phishers (who we will call kit users). Our scheme will thus help investigators to narrow investigation to pervasive phishing criminals. By analyzing the clusters generated using our clustering approach, we can determine the strongest and most pervasive phishers, and phishing kit creators, relationships between phishing kit creators and phishing kit users, and the most dominant phisher of one group. These findings have real-life implication in phishing investigation paradigm.
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
期刊最新文献
$1.00 per RT #BostonMarathon #PrayForBoston: Analyzing fake content on Twitter 10v3.c0ns Modeling malicious domain name take-down dynamics: Why eCrime pays A notation for describing the steps in indicator expansion Monitoring a fast flux botnet using recursive and passive DNS: A case study
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1