Online network traffic classification with incremental learning
Conventional network traffic detection methods based on data mining could not efficiently handle high throughput traffic with concept drift. Data stream mining techniques are able to classify evolving data streams although most techniques require completely labeled data. This paper proposes an impro...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Published: |
Springer Verlag
2016
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/72428/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84970016970&doi=10.1007%2fs12530-016-9152-x&partnerID=40&md5=a6993ee33d55a22bd76faa6e25a23b9c |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |