The Application of Extreme Learning Machines to the Network Intrusion Detection Problem

被引：9
|
作者：
Creech, Gideon [1 ,2 ]
Jiang, Frank [1 ]
机构：
[1] Univ New South Wales, Australian Def Force Acad, Royal Australian Navy, Sydney, NSW 2052, Australia
[2] Royal Austrilian Navy, Canberra, ACT, Australia
来源：
NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2012), VOLS A AND B | 2012年 / 1479卷
关键词：
Multi-layer neural network; intrusion detection systems; pattern recognition; SCHEME;
D O I：
10.1063/1.4756450
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The Extreme Learning Machine (ELM) algorithm conventionally suffers from the inferior batch training performance. In this paper, a new approach to combine ELM outputs is proposed with a view to further develop a persistent IDS. Specifically, this paper proposes the application of an Extreme Learning Machine based approach to the network-based intrusion detection system (IDSs). Good performance is achieved and preliminary results are reported in this paper.
引用
收藏
页码：1506 / 1511
页数：6
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