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Enhance Network Intrusion Detection System by Exploiting BR Algorithm as an Optimal Feature Selection

Enhance Network Intrusion Detection System by Exploiting BR Algorithm as an Optimal Feature Selection

Soukaena Hassan Hashem
Copyright: © 2015 |Pages: 16
ISBN13: 9781466665835|ISBN10: 1466665831|EISBN13: 9781466665842
DOI: 10.4018/978-1-4666-6583-5.ch002
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MLA

Hashem, Soukaena Hassan. "Enhance Network Intrusion Detection System by Exploiting BR Algorithm as an Optimal Feature Selection." Handbook of Research on Threat Detection and Countermeasures in Network Security, edited by Alaa Hussein Al-Hamami and Ghossoon M. Waleed al-Saadoon, IGI Global, 2015, pp. 17-32. https://doi.org/10.4018/978-1-4666-6583-5.ch002

APA

Hashem, S. H. (2015). Enhance Network Intrusion Detection System by Exploiting BR Algorithm as an Optimal Feature Selection. In A. Al-Hamami & G. Waleed al-Saadoon (Eds.), Handbook of Research on Threat Detection and Countermeasures in Network Security (pp. 17-32). IGI Global. https://doi.org/10.4018/978-1-4666-6583-5.ch002

Chicago

Hashem, Soukaena Hassan. "Enhance Network Intrusion Detection System by Exploiting BR Algorithm as an Optimal Feature Selection." In Handbook of Research on Threat Detection and Countermeasures in Network Security, edited by Alaa Hussein Al-Hamami and Ghossoon M. Waleed al-Saadoon, 17-32. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6583-5.ch002

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Abstract

This chapter aims to build a proposed Wire/Wireless Network Intrusion Detection System (WWNIDS) to detect intrusions and consider many of modern attacks which are not taken in account previously. The proposal WWNIDS treat intrusion detection with just intrinsic features but not all of them. The dataset of WWNIDS will consist of two parts; first part will be wire network dataset which has been constructed from KDD'99 that has 41 features with some modifications to produce the proposed dataset that called modern KDD and to be reliable in detecting intrusion by suggesting three additional features. The second part will be building wireless network dataset by collecting thousands of sessions (normal and intrusion); this proposed dataset is called Constructed Wireless Data Set (CWDS). The preprocessing process will be done on the two datasets (KDD & CWDS) to eliminate some problems that affect the detection of intrusion such as noise, missing values and duplication.

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