Intrusion Detection using C4.5: Performance Enhancement by Classifier Combination
نویسندگان
چکیده
Data Security has become a very critical part of any organizational information system. Intrusion Detection System (IDS) is used as a security measure to preserve data integrity and system availability from various attacks. This paper evaluates the performance of C4.5 classifier and its combination using bagging, boosting and stacking over NSLKDD dataset for IDS. This dataset set consists of selected records of the complete KDD dataset.
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تاریخ انتشار 2011