The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The data processed by intrusion detection systems usually is vague, uncertainty, imprecise and incomplete. Rough Set theory is one of the best methods to process this kind of data. But Rough Set theory can only process some discrete data. So the data with continuous numerical attributes must be discretized before they are used. Some current discretization algorithms are classified and reviewed ...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The necessity of efficient intrusion detection system increased recent research to be focused on hybrid techniques for better results. In recent research plenty of intrusion detection systems have been proposed with various data mining techniques, machine learning mechanisms and fuzzy logic. Existing intrusion detection systems suffered from higher false positive rate and negative rate. This pa...

The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). This paper presents two hybrid approaches for modeling IDS. Decision trees (DT) and support vector machines (SVM) are combined as a hierarchical hybrid intelligent system model (DT–SVM) and an ensemble approach combining the base ...