An Novel Intrusion Detection System Based on Naive Bayesian Algorithm
Abstract:
With increasing Internet connectivity and traffic volume,
recent intrusion incidents have reemphasized the importance of network Intrusion
Detection System (IDS). According to the deficiency of the Naive Bayesian (NB)
algorithm, this paper presents an improved NB algorithm, which is addition of
an attribute-added method to the traditional NB. This algorithm which is based
on the original model and combined with a controlling parameter to enhance the
accuracy of classification, the best parameter obtained by experiments can not
only simplify both the time complexity and space complexity of the intrusion
detection but also optimize the classification performance. The experimental
results prove that this proposed approach applied into the intrusion detection
framework can drastically reduce the false alarm rate of IDS so as to improve
the detection efficiency and decrease economic damage brought by the cyber attack.
How to cite this article
Hui Wang, Hongyu Chen and Shanshan Yang, 2013. An Novel Intrusion Detection System Based on Naive Bayesian Algorithm. Journal of Applied Sciences, 13: 1865-1870.
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