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Recently, DoS (Denial of Service) detection has become more and more important in web security. In this paper, we argue that DoS attack can be taken as continuous data streams, and thus can be detected by using stream data mining methods. More specifically, we propose a new Weighted Ensemble learning model to detect the DoS attacks. The Weighted Ensemble(More)
Peer-to-Peer (P2P) networks have been widely applied in file sharing, streaming media, instant messaging and other fields, which have attracted large attention. At the same time P2P networks traffic worsens the congestion of a network significantly. In order to better manage and control P2P traffic, it is important to identify P2P traffic accurately. In(More)
Bayesian harmonic modeling and parameters estimation is a new approach in audio signal synthesizing. However current Bayesian harmonic modeling canpsilat effectively extract high frequency partials. In this paper we propose an improved model with parameters of high frequency partials for audio signal with harmonic modeling. We estimate partials in a(More)
Accurate classification of traffic flows is highly beneficial for network management and security monitoring. Nowadays, many researchers have proposed machine learning techniques (i.e., decision tree, SVM, BayesNet and Naïve Bayes) for traffic classification. However, none of these classification techniques can achieve the highest accuracy for all(More)
Related data streams refer to data streams that can be joined together by matching their join attributes. Existing research on learning from related data streams is based on an assumption that all streams arrive at a central processing unit in a synchronous way, such that in an arbitrary sliding window, all tuples of the streams can be perfectly joined(More)
—Recently, Peer-to-peer (P2P) networks have been widely applied in streaming media, instant messaging, file sharing and other fields, which have occupied more and more network bandwidth. Accurately identify P2P traffic is very important to management and control P2P traffic. In this paper, we introduce HFBP, a novel P2P identification scheme based on the(More)
Online traffic classification has been widely used in quality of service measurements, network management and security monitoring. Currently, more and more research works tend to apply machine learning techniques to online traffic classification, and most of them are based on supervised learning and unsupervised learning techniques. Although supervised(More)
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