Evaluation effectiveness of hybrid IDS using Snort with Naïve Bayes to detect attacks
作者： Safwan Mawlood Hussein , Fakariah Hani Mohd Ali , Zolidah Kasiran
DOI: 10.1109/DICTAP.2012.6215386
关键词:
摘要: The enormous number of attacks over the Internet nowadays makes information under potential violation. Intrusion Detection System (IDS) is used as second line defense to observe suspicious actions going on in computers or network devices. IDS have two approaches by using only one misuse anomaly can be detected. This research proposed hybrid integrated signature based (Snort) with (Naive Bayes) enhance system security detect attacks. Knowledge Discovery Data Mining (KDD) CUP 99 dataset and Waikato Environment for Analysis (WEKA) program testing IDS. Accuracy, detection rate, time build model false alarm rate were parameters evaluate performance between Snort Naive Bayes, J48graft Bayes Net. result shows good algorithm.
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