DocumentCode
2494711
Title
Research Intrusion Detection Techniques from the Perspective of Machine Learning
Author
Hui, Liu ; Cao Yonghui
Author_Institution
Sch. of Comput. & Inf. Technol., Henan Normal Univ., Xinxiang, China
Volume
1
fYear
2010
fDate
24-25 April 2010
Firstpage
166
Lastpage
168
Abstract
With the rapid development of the Internet services and the fast increasing of intrusion problems, the traditional intrusion detection methods cannot work well with the more and more complicated intrusions. So introducing machine learning into intrusion detection systems to improve the performance has become one of the major concerns in the research of intrusion detection. Intrusion detection systems were proposed to complement prevention-based security measures. In this paper, we first introduces the basic structure of the intrusion detection system, then analysis intrusion Detection Techniques Based on Machine Learning Method, including the Bayesian based method, the neural network based method, the data mining based method and the SVM based method.
Keywords
Bayes methods; Internet; data mining; learning (artificial intelligence); neural nets; security of data; support vector machines; Bayesian based method; Internet services; SVM based method; data mining based method; intrusion detection techniques; machine learning; neural network based method; prevention based security measures; Bayesian methods; Data mining; Data security; Information technology; Intrusion detection; Learning systems; Machine learning; Neural networks; Support vector machines; Web and internet services;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Information Technology (MMIT), 2010 Second International Conference on
Conference_Location
Kaifeng
Print_ISBN
978-0-7695-4008-5
Electronic_ISBN
978-1-4244-6602-3
Type
conf
DOI
10.1109/MMIT.2010.161
Filename
5474252
Link To Document