A Dataset for Evaluating Intrusion Detection Systems in IEEE 802.11 Wireless Networks

被引：0

作者：

Vilela, Douglas W. F. L. ^{[1
]}

Ferreira, Ed' Wilson T. ^{[1
]}

Shinoda, Ailton Akira ^{[1
]}

Araujo, Nelcileno V. de Souza ^{[2
]}

de Oliveira, Ruy ^{[3
]}

Nascimento, Valtemir E. ^{[3
]}

机构：

[1] Univ Estadual Paulista, Dept Engn Eletr, Ilha Solteira, Brazil

[2] Univ Fed Mato Grosso, Inst Comp, Cuiaba, Brazil

[3] Inst Fed Mato Grosso, Dept Area Informat, Cuiaba, Brazil

来源：

2014 IEEE COLOMBIAN CONFERENCE ON COMMUNICATIONS AND COMPUTING (COLCOM) | 2014年

关键词：

Dataset; security; pattern classification; neural networks; Bayes Net;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Internet access by wireless networks has grown considerably in recent years. However, these networks are vulnerable to security problems, especially those related to denial of service attacks. Intrusion Detection Systems(IDS)are widely used to improve network security, but comparison among the several existing approaches is not a trivial task. This paper proposes building a datasetfor evaluating IDS in wireless environments. The data were captured in a real, operating network. We conducted tests using traditional IDS and achieved great results, which showed the effectiveness of our proposed approach.

引用

页数：5

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