Efficient Model for Intrusion Detection using Enhanced Classification Technique
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International Journal of Engineering Trends and Technology (IJETT) | 
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| © 2017 by IJETT Journal | ||
| Volume-51 Number-2 |
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| Year of Publication : 2017 | ||
| Authors : Elsayed A.Elhafeez, Amr M. Gody, Tamer M. Barakat, Ayman. I. Madbouly |
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| DOI : 10.14445/22315381/IJETT-V51P213 |
Citation
Elsayed A.Elhafeez, Amr M. Gody, Tamer M. Barakat, Ayman. I. Madbouly "Efficient Model for Intrusion Detection using Enhanced Classification Technique", International Journal of Engineering Trends and Technology (IJETT), V51(2),70-77 September 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
False alerts are the most major problem that disturbs network administrator. In spite of the intelligent methods and strategy used by intrusion detection system, elimination of false alerts is still a big challenge. Due to the huge amount of information transmitted through the network, the traffic contains a big amount of redundant and duplicated information. That leads to bias the classifier and decrease classification accuracy and increase false alerts. So, we proposed an enhanced model to eliminate false alerts whether it was false positive or false negative alerts and increase the accuracy of intrusion detection system.
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Keywords
IDS, false positive alerts, false negative alerts.