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.