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


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.



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

Como citar

2014 Ieee Colombian Conference On Communications And Computing (colcom). New York: Ieee, 5 p., 2014.