CLEAN:基于被动DNS流量检测良性域名的一种方法

Chunyu Han, Yongzheng Zhang
{"title":"CLEAN:基于被动DNS流量检测良性域名的一种方法","authors":"Chunyu Han, Yongzheng Zhang","doi":"10.1109/ICCSNT.2017.8343715","DOIUrl":null,"url":null,"abstract":"Domain name plays a crucial role on the Internet. Therefore, more and more malicious behavior had been conducted by using the domain name, such as spam, botnet, phishing and the like. Thus, lots of research have been done for detecting these malicious domain names. Nevertheless, the effort focused on benign domain names is little. It is obvious that finding more benign domain names accurately is very helpful for detecting malicious domain names. In this paper, we analyze a great number of domain names and propose a method, CLEAN(CLassifier of bEnign domAin Names), for discovering benign domain names from plenty of domain names on the passive DNS traffic. Eventually, we conducted the experiment to check the effect. The result showed the recall rate is 82.1% and accuracy rate is 92.2%.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"CLEAN : An approach for detecting benign domain names based on passive DNS traffic\",\"authors\":\"Chunyu Han, Yongzheng Zhang\",\"doi\":\"10.1109/ICCSNT.2017.8343715\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Domain name plays a crucial role on the Internet. Therefore, more and more malicious behavior had been conducted by using the domain name, such as spam, botnet, phishing and the like. Thus, lots of research have been done for detecting these malicious domain names. Nevertheless, the effort focused on benign domain names is little. It is obvious that finding more benign domain names accurately is very helpful for detecting malicious domain names. In this paper, we analyze a great number of domain names and propose a method, CLEAN(CLassifier of bEnign domAin Names), for discovering benign domain names from plenty of domain names on the passive DNS traffic. Eventually, we conducted the experiment to check the effect. The result showed the recall rate is 82.1% and accuracy rate is 92.2%.\",\"PeriodicalId\":163433,\"journal\":{\"name\":\"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSNT.2017.8343715\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSNT.2017.8343715","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

域名在互联网中起着至关重要的作用。因此,利用域名进行的恶意行为越来越多,如垃圾邮件、僵尸网络、网络钓鱼等。因此,人们对这些恶意域名的检测进行了大量的研究。然而,关注良性域名的努力很少。很明显,准确地找到更多的良性域名对于检测恶意域名是非常有帮助的。本文通过对大量域名的分析,提出了一种从被动DNS流量中大量域名中发现良性域名的方法——CLEAN(bEnign domain names CLassifier)。最后,我们进行了实验来检验效果。结果表明,召回率为82.1%,准确率为92.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CLEAN : An approach for detecting benign domain names based on passive DNS traffic
Domain name plays a crucial role on the Internet. Therefore, more and more malicious behavior had been conducted by using the domain name, such as spam, botnet, phishing and the like. Thus, lots of research have been done for detecting these malicious domain names. Nevertheless, the effort focused on benign domain names is little. It is obvious that finding more benign domain names accurately is very helpful for detecting malicious domain names. In this paper, we analyze a great number of domain names and propose a method, CLEAN(CLassifier of bEnign domAin Names), for discovering benign domain names from plenty of domain names on the passive DNS traffic. Eventually, we conducted the experiment to check the effect. The result showed the recall rate is 82.1% and accuracy rate is 92.2%.
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