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Malicious intrusion is the behavior that threats a large number of computers; therefore, recent research has focused on devising new techniques to detect and control internet intrusion with high efficiency and low cost. Unfortunately some anomaly detection system (ADS) over machine learning may get some false alarms if the results of machine learning cannot cover all the normal or abnormal data. In...
In this study, a novel classifier ensemble method named adaptive nonparametric weighted feature extraction (AdaNWFE) is proposed. This new concept is deduced from AdaBoost and NWFE. The main idea of AdaNWFE is adaptive in the sense that subsequent feature spaces are tweaked in favor of those instances misclassified by classifiers in the previous feature space. All training samples are projected to...
The machine learning is certificated as one of the most important technologies in todaypsilas world. There are several various researches applying machine learning to improve its operation efficiency in many different aspects.Based on the social science citation index (SSCI) database,this research is using text mining technology which collecting the homogeneous glossaries in the articles, conducting...
High false alarm rate and time-space cost of rule extraction and detection limit the application of machine learning in real intrusion detection system (IDS), and IDS cannot satisfy most system performance requirements simultaneously. In this paper, a Constraint-based gene expression programming rule extraction algorithm (CGREA) is proposed which guarantees the validity of rules and reduces the evolution...
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