Intrusion detection system based on data mining techniques to reduce false alarm rate
Joint Authors
Sharif, Sarah Muhammad
Hashim, Sukaynah Hasan
Source
Engineering and Technology Journal
Issue
Vol. 36, Issue 2B (28 Feb. 2018), pp.110-119, 10 p.
Publisher
Publication Date
2018-02-28
Country of Publication
Iraq
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Nowadays, Security of network traffic is becoming a major issue of computer network system according to the huge development of internet.
Intrusion detection system has been used for discovering intrusion and to maintain the security information from attacks.
In this paper, produced two levels of mining algorithms to construct Network Intrusion Detection System (NIDS) and to reduce false alarm rate, in the first level Naïve Bayes algorithm is used to classify abnormal activity into the main four attack types from normal behavior.
In the second level ID3 decision tree algorithm is used to classify four attack types into (22) children of attacks from normal behavior.
To evaluate the performance of the two proposed algorithms by using kdd99 dataset intrusion detection system and the evaluation metric accuracy, precision, DR, F-measure.
The experimental results prove that the proposal system done high detection rates (DR) of 99 % and reduce false positives (FP) of 0 % for different types of network intrusions
American Psychological Association (APA)
Sharif, Sarah Muhammad& Hashim, Sukaynah Hasan. 2018. Intrusion detection system based on data mining techniques to reduce false alarm rate. Engineering and Technology Journal،Vol. 36, no. 2B, pp.110-119.
https://search.emarefa.net/detail/BIM-899532
Modern Language Association (MLA)
Sharif, Sarah Muhammad& Hashim, Sukaynah Hasan. Intrusion detection system based on data mining techniques to reduce false alarm rate. Engineering and Technology Journal Vol. 36, no. 2B (2018), pp.110-119.
https://search.emarefa.net/detail/BIM-899532
American Medical Association (AMA)
Sharif, Sarah Muhammad& Hashim, Sukaynah Hasan. Intrusion detection system based on data mining techniques to reduce false alarm rate. Engineering and Technology Journal. 2018. Vol. 36, no. 2B, pp.110-119.
https://search.emarefa.net/detail/BIM-899532
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 119
Record ID
BIM-899532