A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Robust network traffic identification with unknown applications
2013
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and communications security - ASIA CCS '13
Traffic classification is a fundamental component in advanced network management and security. Recent research has achieved certain success in the application of machine learning techniques into flow statistical feature based approach. However, most of flow statistical feature based methods classify traffic based on the assumption that all traffic flows are generated by the known applications. Considering the pervasive unknown applications in the real world environment, this assumption does not
doi:10.1145/2484313.2484366
dblp:conf/ccs/ZhangCXZ13
fatcat:er2chtmmfrgihf6kev7h2gtnhi