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Mass of the training samples and setting parameters of SVM artificially will affect badly the efficiency to find an optimal decision hyper plane for SVM. In this paper, FCM clustering algorithm and heuristic PSO algorithm are applied to Intrusion Detection. FCM clustering algorithm is designed to help SVM to find the optimal training samples from vast amounts of data; heuristic PSO algorithm is designed...
Internet security is seriously threatened by spam spreading, and content-based spam filtering has become one of effective spam-filtering methods. Aiming at the practical problems, we propose an active learning based method which takes naive Bayesian means as basic classifiers. This method randomly initialize a small training set to generate basic classifiers, and then use them to classify mails, which...
It is important that the training time of the Support Vector Machine (SVM) is shortened and storage space requirement is reduced for high-speed and large-scale network. An intrusion detection method based on parallel SVM is proposed and a detection model system is constructed in this paper. First, original training dataset gained from network is divided into three subsets according to the network...
Dynamical analysis of the current network status is critical to detect large scale intrusions and to ensure the networks to continually function. Collecting and analyzing traffic in real time and reporting the current status in time provide a feasible way. In this paper we used a refined naive Bayes method, naive Bayes kernel estimator (NBKE), to identify flooding attacks and port scans from normal...
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