{"title":"CODDULM:一种在被动DNS流量中检测DGA C&C域的方法","authors":"Chunyu Han, Yongzheng Zhang","doi":"10.1109/ICCSNT.2017.8343724","DOIUrl":null,"url":null,"abstract":"Domain plays an important role as one of the components on the Internet, so more and more malicious behavior has been conducted by using domains, such as spam, botnet, phishing and the like. DGA (Domain Generation Algorithm), one kind of DNS technology, has been used by domain-flux commonly in botnets. In this paper, we propose a method called CODDULM (C&c domains Of Dga Detection Using Lexical feature and sparse Matrix). Firstly, it finds the NXDomains (Non-existent domains) on the passive DNS traffic to locate the suspicious infected hosts. Secondly, it selects DGA domains by lexical features according to suspicious infected hosts. Lastly, it discovers DGA C&C (Command and Control) domains through SVM (Support Vector Machine algorithm) classifier. At the end of this paper, we conduct the experiment to verify the effect of the method and the high accuracy of it.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"CODDULM: An approach for detecting C&C domains of DGA on passive DNS traffic\",\"authors\":\"Chunyu Han, Yongzheng Zhang\",\"doi\":\"10.1109/ICCSNT.2017.8343724\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Domain plays an important role as one of the components on the Internet, so more and more malicious behavior has been conducted by using domains, such as spam, botnet, phishing and the like. DGA (Domain Generation Algorithm), one kind of DNS technology, has been used by domain-flux commonly in botnets. In this paper, we propose a method called CODDULM (C&c domains Of Dga Detection Using Lexical feature and sparse Matrix). Firstly, it finds the NXDomains (Non-existent domains) on the passive DNS traffic to locate the suspicious infected hosts. Secondly, it selects DGA domains by lexical features according to suspicious infected hosts. Lastly, it discovers DGA C&C (Command and Control) domains through SVM (Support Vector Machine algorithm) classifier. At the end of this paper, we conduct the experiment to verify the effect of the method and the high accuracy of it.\",\"PeriodicalId\":163433,\"journal\":{\"name\":\"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)\",\"volume\":\"78 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"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.2017.8343724\",\"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.2017.8343724","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CODDULM: An approach for detecting C&C domains of DGA on passive DNS traffic
Domain plays an important role as one of the components on the Internet, so more and more malicious behavior has been conducted by using domains, such as spam, botnet, phishing and the like. DGA (Domain Generation Algorithm), one kind of DNS technology, has been used by domain-flux commonly in botnets. In this paper, we propose a method called CODDULM (C&c domains Of Dga Detection Using Lexical feature and sparse Matrix). Firstly, it finds the NXDomains (Non-existent domains) on the passive DNS traffic to locate the suspicious infected hosts. Secondly, it selects DGA domains by lexical features according to suspicious infected hosts. Lastly, it discovers DGA C&C (Command and Control) domains through SVM (Support Vector Machine algorithm) classifier. At the end of this paper, we conduct the experiment to verify the effect of the method and the high accuracy of it.