By Topic

Statistical analysis of local features in network traffic processes

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)
Giorgi, G. ; Dept. of Inf. Eng., Padova Univ. ; Narduzzi, C. ; Pegoraro, P.A.

This work presents an approach to the detection of local features in network traffic, based on the analysis of short-time maximal rate envelopes, also called statistical arrival curves. In the proposed method, the time series representing a traffic trace is divided into non-overlapping segments, which are further divided into smaller blocks. The maximal rate envelope is estimated for each block and histograms of rate parameters are built over each segment. When significant local features are present in a trace segment, values of the maximal rates may change, resulting in the appearance of peaks or long tails in the corresponding histograms. These effects can be detected with remarkable sensitivity, since they are often evidenced by positive or negative peaks in skewness values of rate parameters histograms. The algorithm can be employed to detect such features on a reasonably fine-grained scale

Published in:

Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on

Date of Conference:

17-20 July 2005