Comparison of NBTree and VFI Machine Learning Algorithms for Network Intrusion Detection using Feature Selection

作者: Rupali Malviya , Brajesh K. Umrao

DOI: 10.5120/18886-0165

关键词:

摘要: But, with the proliferation of electronic devices and internet, there has been an exponential rise in malicious activities. The security perpetrators take advantage intricacy internet carry out intrusions. There have certain researches to find solutions for detecting In this paper, research application machine learning techniques field network intrusion detection. Machine can learn normal anomalous patterns from training data generate classifiers which be used detect intrusions a network. are Naive Bayes Tree algorithm Voting Feature Intervals algorithm. Also, Selection Methods improve performance these algorithms were because input is high dimension feature space, but all features available not relevant classification. Two approaches taken into consideration selection, Chi Square Gain Ratio. Using selection comparative study two NBTree VFI as done. NSL-KDD set train test classifiers.

参考文章(19)
Robert S. Sielken, Anita K. Jones, Computer System Intrusion Detection: A Survey ,(2000)
Ron Kohavi, Scaling up the accuracy of Naive-Bayes classifiers: a decision-tree hybrid knowledge discovery and data mining. pp. 202- 207 ,(1996)
Mark A. Hall, Ian H. Witten, Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques ,(1999)
Kevin Thompson, Pat Langley, and Wayne Iba, An analysis of Bayesian classifiers national conference on artificial intelligence. pp. 223- 228 ,(1992)
Sandeep V. Sabnani, Andreas Fuchsberger, Computer Security: A Machine Learning Approach ,(2008)
Levent Ertoz, Aleksandar Lazarevic, Paul Dokas, Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava, Data Mining for Network Intrusion Detection ,(2002)
Gülşen Demiröz, H. Altay Güvenir, Classification by Voting Feature Intervals european conference on machine learning. pp. 85- 92 ,(1997) , 10.1007/3-540-62858-4_74
Gary Stein, Bing Chen, Annie S. Wu, Kien A. Hua, Decision tree classifier for network intrusion detection with GA-based feature selection Proceedings of the 43rd annual southeast regional conference on - ACM-SE 43. pp. 136- 141 ,(2005) , 10.1145/1167253.1167288
Avrim L. Blum, Pat Langley, Selection of relevant features and examples in machine learning Artificial Intelligence. ,vol. 97, pp. 245- 271 ,(1997) , 10.1016/S0004-3702(97)00063-5