Publicação: A dataset for evaluating intrusion detection systems in IEEE 802.11 wireless networks
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Internet access by wireless networks has grownconsiderably 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 paperproposes building a datasetfor evaluating IDS in wireless environments. The data were captured in a real, operating network. We conducted tests using traditional IDS and achievedgreat results, which showed the effectiveness of our proposed approach. © 2014 IEEE.
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Bayes Net, Dataset, neural networks, pattern classification, security
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Inglês
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2014 IEEE Colombian Conference on Communications and Computing, COLCOM 2014 - Conference Proceedings.
