Chaxiong Yukonhiatou, S. Kittitornkun, Hiroaki Kikuchi, Khamphao Sisaat, M. Terada, H. Ishii
{"title":"基于下载行为的前10名恶意软件/机器人聚类","authors":"Chaxiong Yukonhiatou, S. Kittitornkun, Hiroaki Kikuchi, Khamphao Sisaat, M. Terada, H. Ishii","doi":"10.1109/ICITEED.2013.6676212","DOIUrl":null,"url":null,"abstract":"Malware can be spread over the Internet via especially download mechanism to the victim computers. This work tries to cluster malware/bots download behavior of Top-10 malware based on 2010 and 2011 CCC (Cyber Clean Center) datasets. The datasets contain more than one million download logs collected from several independent honeypots in Japan to observe malware/bot traffic and activities. Although the daily and hourly patterns are quite similar in 2010, those of 2011 are quite different. As a result, the proposed Integral Correlation Coefficient can cluster 3 and 4 groups of Top-10 malware/bots in 2010 and 2011, respectively.","PeriodicalId":204082,"journal":{"name":"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Clustering Top-10 malware/bots based on download behavior\",\"authors\":\"Chaxiong Yukonhiatou, S. Kittitornkun, Hiroaki Kikuchi, Khamphao Sisaat, M. Terada, H. Ishii\",\"doi\":\"10.1109/ICITEED.2013.6676212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Malware can be spread over the Internet via especially download mechanism to the victim computers. This work tries to cluster malware/bots download behavior of Top-10 malware based on 2010 and 2011 CCC (Cyber Clean Center) datasets. The datasets contain more than one million download logs collected from several independent honeypots in Japan to observe malware/bot traffic and activities. Although the daily and hourly patterns are quite similar in 2010, those of 2011 are quite different. As a result, the proposed Integral Correlation Coefficient can cluster 3 and 4 groups of Top-10 malware/bots in 2010 and 2011, respectively.\",\"PeriodicalId\":204082,\"journal\":{\"name\":\"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEED.2013.6676212\",\"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 International Conference on Information Technology and Electrical Engineering (ICITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEED.2013.6676212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clustering Top-10 malware/bots based on download behavior
Malware can be spread over the Internet via especially download mechanism to the victim computers. This work tries to cluster malware/bots download behavior of Top-10 malware based on 2010 and 2011 CCC (Cyber Clean Center) datasets. The datasets contain more than one million download logs collected from several independent honeypots in Japan to observe malware/bot traffic and activities. Although the daily and hourly patterns are quite similar in 2010, those of 2011 are quite different. As a result, the proposed Integral Correlation Coefficient can cluster 3 and 4 groups of Top-10 malware/bots in 2010 and 2011, respectively.