Use Cases of Applying Machine Learning Mechanism with Network Traffic
draft-jiang-nmlrg-traffic-machine-learning-00
| Document | Type | Expired Internet-Draft (individual) | |
|---|---|---|---|
| Authors | Sheng Jiang , Bing Liu , Panagiotis Demestichas , Jérôme François , Giovane Moura , Pere Barlet | ||
| Last updated | 2016-12-05 (Latest revision 2016-06-03) | ||
| Stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats |
Expired & archived
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| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
https://www.ietf.org/archive/id/draft-jiang-nmlrg-traffic-machine-learning-00.txt
Abstract
This document introduces a set of use cases in which machine learning technologies are applied to network traffic relevant activities, including machine learning based traffic classification, traffic management, etc.
Authors
Sheng Jiang
Bing Liu
Panagiotis Demestichas
Jérôme François
Giovane Moura
Pere Barlet
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)