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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/117644
Title: 
A Dataset for Evaluating Intrusion Detection Systems in IEEE 802.11 Wireless Networks
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
Abstract: 
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.
Issue Date: 
1-Jan-2014
Citation: 
2014 Ieee Colombian Conference On Communications And Computing (colcom). New York: Ieee, 5 p., 2014.
Time Duration: 
5
Publisher: 
Ieee
Keywords: 
  • Dataset
  • security
  • pattern classification
  • neural networks
  • Bayes Net
Source: 
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6860434&punumber%3D6851796%26sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6860394%29%26pageNumber%3D2
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/117644
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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