Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Conference paper
Title: Distributed Detection of Network Intrusions Based on a Parametric Model
Author: Wang, Y.
Li, X.
Hu, W.
Citation: IEEE International Conference on Systems, Man and Cybernetics, 2008 - Proceedings: pp.2069-2074
Publisher: IEEE
Publisher Place: Online
Issue Date: 2008
ISBN: 9781424423842
ISSN: 1062-922X
Conference Name: IEEE International Conference on Systems, Man and Cybernetics (2008 : Singapore)
Statement of
Yan-guo Wang, Xi Li, and Weiming Hu
Abstract: With the increasing requirements of fast response and privacy protection, how to detect network intrusions in a distributed architecture becomes a hot research area in the development of modern information security systems. However, it is a challenge to build such a system, given the difficulties brought by the mixed-attribute property of network connection data and the constraints on network communication. In this paper, we present a framework for distributed detection of network intrusions based on a parametric model. The parametric model can explicitly reflect the distributions of different intrusion types and handle the mixed-attribute data naturally. Based on the model, we can generate an accurate global intrusion detector with a very low cost of communication among the distributed detection sites, and no sharing of original network data is needed. Experimental results demonstrate the advantages of the proposed framework in the distributed intrusion detection application.
Keywords: Distributed detection; machine learning; information security
Rights: ©2008 IEEE
RMID: 0020112697
DOI: 10.1109/ICSMC.2008.4811596
Description (link):
Appears in Collections:Computer Science publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.