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An Intrusion Detection System (IDS) is a crucial element of a network security posture. One class of IDS, called signature-based network IDSs, monitors network traffic, looking for evidence of malicious behavior as specified in attack descriptions (referred to as signatures). Many studies have reported that IDSs can generate thousands of alarms a day, many of which are false alarms. The problem often...
The 3 most important issues for anomaly detection based intrusion detection systems by using data mining methods are: feature selection, data value normalization, and the choice of data mining algorithms. In this paper, we study primarily the feature selection of network traffic and its impact on the detection rates. We use KDD CUP 1999 dataset as the sample for the study. We group the features of...
Selecting suitable features is very crucial for achieving successful classification of land cover types. This paper presents a comparative study of three typical feature selection methods for the task of regional land cover classification using MODIS data. Comparison results have shown that Branch and Bound is the best for land cover classification with MODIS data, while ReliefF and mRMR achieve nearly...
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