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New Trends in Intrusion Awareness System Based on SVM Classification


Chandra Prakash Bhargava, Gajendra Singh Chandel


Vol. 14  No. 9  pp. 71-73


Network intrusion awareness is important factor for risk analysis of network security. In the current decade various method and framework are available for intrusion detection and security awareness. Some method based on knowledge discovery process and some framework based on neural network. These entire model take rule based decision for the generation of security alerts. In this paper we proposed a novel method for intrusion awareness using data fusion and SVM classification. Data fusion work on the biases of features gathering of event. Support vector machine is super classifier of data. Here we used SVM for the detection of closed item of ruled based technique. Our proposed method simulate on KDD1999 DARPA data set and get better empirical evaluation result in comparison of rule based technique and neural network model


intrusion awareness, data fusion, SVM and KDDCUP1999