http://iet.metastore.ingenta.com
1887

## Conclusion

• Author(s):
• DOI:

$16.00 (plus tax if applicable) ##### Buy Knowledge Pack 10 chapters for$120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:

Network Classification for Traffic Management: Anomaly detection, feature selection, clustering and classification — Recommend this title to your library

## Thank you

Network traffic classification has the potential to resolve key issues for network operators, including network management problems, quality of service provisioning, Internet accounting and charging, and lawful interception [1]. The traditional network classification techniques that rely mostly on well-known port numbers have been used to identify Internet traffic. Such an approach was successful because traditional applications used fixed port numbers; however [9,10] show that the current generations of peer-to-peer (P2P) applications try to hide their traffic by using dynamic port numbers. Consequently, applications whose port numbers are unknown cannot be identified in advance.

Chapter Contents:

• 11 Conclusion
• 11.1 Contribution
• 11.2 Future work

Preview this chapter:

Conclusion, Page 1 of 2

| /docserver/preview/fulltext/books/pc/pbpc032e/PBPC032E_ch11-1.gif /docserver/preview/fulltext/books/pc/pbpc032e/PBPC032E_ch11-2.gif

### Related content

content/books/10.1049/pbpc032e_ch11
pub_keyword,iet_inspecKeyword,pub_concept
6
6
This is a required field