{"title":"BitMiner: Bits Mining in Internet Traffic Classification","authors":"Zhenlong Yuan, Y. Xue, M. Schaar","doi":"10.1145/2785956.2789997","DOIUrl":null,"url":null,"abstract":"Traditionally, signatures used for traffic classification are constructed at the byte-level. However, as more and more data-transfer formats of network protocols and applications are encoded at the bit-level, byte-level signatures are losing their effectiveness in traffic classification. In this poster, we creatively construct bit-level signatures by associating the bit-values with their bit-positions in each traffic flow. Furthermore, we present BitMiner, an automated traffic mining tool that can mine application signatures at the most fine-grained bit-level granularity. Our preliminary test on popular peer-to-peer (P2P) applications, e.g. Skype, Google Hangouts, PPTV, eMule, Xunlei and QQDownload, reveals that although they all have no byte-level signatures, there are significant bit-level signatures hidden in their traffic.","PeriodicalId":268472,"journal":{"name":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2785956.2789997","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Traditionally, signatures used for traffic classification are constructed at the byte-level. However, as more and more data-transfer formats of network protocols and applications are encoded at the bit-level, byte-level signatures are losing their effectiveness in traffic classification. In this poster, we creatively construct bit-level signatures by associating the bit-values with their bit-positions in each traffic flow. Furthermore, we present BitMiner, an automated traffic mining tool that can mine application signatures at the most fine-grained bit-level granularity. Our preliminary test on popular peer-to-peer (P2P) applications, e.g. Skype, Google Hangouts, PPTV, eMule, Xunlei and QQDownload, reveals that although they all have no byte-level signatures, there are significant bit-level signatures hidden in their traffic.