Analysis of Machine Learning Techniques for Intrusion Detection System: A Review

Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from ne...

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Bibliographic Details
Published in:International journal of computer applications 2015-01, Vol.119 (3), p.19-29
Main Authors: AliShah, Asghar, Sikander Hayat Khiyal, Malik, Daud Awan, Muhammad
Format: Article
Language:English
Subjects:
Classifiers
Computer information security
Computer networks
Intrusion
Machine learning
Networks
Online Access:Get full text
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Summary:Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks. Various Machine learning techniques are used in IDS. This study analyzes machine learning techniques in IDS. It also reviews many related studies done in the period from 2000 to 2012 and it focuses on machine learning techniques. Related studies include single, hybrid, ensemble classifiers, baseline and datasets used.
ISSN:0975-8887
0975-8887
DOI:10.5120/21047-3678