Hybrid fuzzy logic and artificial bee colony algorithm for intrusion detection and classification
Other Title(s)
تهجين المنطق المضبب و خوارزمية مستعمرة النحل الذكي لكشف و تصنيف التطفل
Author
Source
Issue
Vol. 57, Issue 1A (31 Mar. 2016), pp.241-252, 12 p.
Publisher
University of Baghdad College of Science
Publication Date
2016-03-31
Country of Publication
Iraq
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Topics
- Computer networks
- Intrusion detection systems(Computer security)
- Artificial bee colony algorithm
- Fuzzy logic
Abstract EN
In recent years, with the growing size and the importance of computer networks, it is very necessary to provide adequate protection for users data from snooping through the use of one of the protection techniques: encryption, firewall and intrusion detection systems etc.
Intrusion detection systems is considered one of the most important components in the computer networks that deal with Network security problems.
In this research, we suggested the intrusion detection and classification system through merging Fuzzy logic and Artificial Bee Colony Algorithm.
Fuzzy logic has been used to build a classifier which has the ability to distinguish between the behavior of the normal user and behavior of the intruder.
The artificial bee colony algorithm has been used to build the classifier which was used to classify the intrusion into one of the main types (DoS, R2L , U2R, Prob).
The proposed system has the ability to detect and classify intrusion at high speed with a small percentage of false alarms as well as to detect the new attacks.
The NSL-KDD dataset used in the training and testing the proposed system.The results of experiments showed that the efficiency of the proposed system performance were (97.59%) for the intrusion detection, and (0.12%) for the false alarms.
Also, the Classification rates for classes (DoS, R2L,U2R,Prob) were (97.19, 77.09, 98.43, 93.23) Respectively, which is considered a superior performance comparing with other methods in the literature.
American Psychological Association (APA)
Mahmud, Mahmud Subhi. 2016. Hybrid fuzzy logic and artificial bee colony algorithm for intrusion detection and classification. Iraqi Journal of Science،Vol. 57, no. 1A, pp.241-252.
https://search.emarefa.net/detail/BIM-689880
Modern Language Association (MLA)
Mahmud, Mahmud Subhi. Hybrid fuzzy logic and artificial bee colony algorithm for intrusion detection and classification. Iraqi Journal of Science Vol. 57, no. 1A (2016), pp.241-252.
https://search.emarefa.net/detail/BIM-689880
American Medical Association (AMA)
Mahmud, Mahmud Subhi. Hybrid fuzzy logic and artificial bee colony algorithm for intrusion detection and classification. Iraqi Journal of Science. 2016. Vol. 57, no. 1A, pp.241-252.
https://search.emarefa.net/detail/BIM-689880
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 251-252
Record ID
BIM-689880