International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Open Access | Double Blind Reviewed

ISSN: 2319-7064


Downloads: 95

Survey Paper | Information Technology | India | Volume 3 Issue 6, June 2014


Analysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection System

Macdonald Mukosera [4] | Thabiso Peter Mpofu [6] | Budwell Masaiti [2]


Abstract: In a bid to provide useful information for intrusion detection; we focused on analyzing the NSL-KDD dataset. In this analysis; we seek to simplify the process of mining fuzzy rules by reducing the features and categorizing the dataset into various smaller clusters as smaller units of the dataset are easier to work with than the whole single large dataset. It is less complex to observe and discover sound fuzzy rules from a smaller dataset and this work serves as a foundation to a fuzzy logic based intrusion detection system. This paper presents a methodology for data preprocessing towards an intrusion detection system and Microsoft excel was used in the process.


Keywords: Fuzzy rules, fuzzy logic, intrusion, NSL-KDD dataset, mining


Edition: Volume 3 Issue 6, June 2014,


Pages: 1479 - 1482


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How to Cite this Article?

Macdonald Mukosera, Thabiso Peter Mpofu, Budwell Masaiti, "Analysis of NSL-KDD Dataset for Fuzzy Based Intrusion Detection System", International Journal of Science and Research (IJSR), Volume 3 Issue 6, June 2014, pp. 1479-1482, https://www.ijsr.net/get_abstract.php?paper_id=2014526

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