By Topic

Research of P2P Traffic Identification Based on BP Neural Network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Shen Fuke ; East China Normal Univ. Shanghai 200062, Shanghai ; Change Pan ; Ren Xiaoli

Today's P2P application is a big challenge to network traffic workload. In contrast to first generation P2P networks which used well-defined port numbers, current P2P applications have ability to disguise their existence through the use of arbitrary ports. Our goal is to give out a new approach for P2P traffic identification based BP Neural Network, and without relying on keyword matching. This article introduces BP algorithm, analyzes the characters of P2P traffic, gives out the BP network based on connection patterns ofP2P networks. The trained BPNN was applied as a P2P traffic identifier, which can be used to distinguish any kind of P2P applications from non-P2P applications. This feasible solution has many advantages in P2P traffic identification. We believe our approach is the first method for characterizing P2P traffic using network dynamics based on BP network rather than any userpayload.

Published in:

Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on  (Volume:2 )

Date of Conference:

26-28 Nov. 2007