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The Network Address Translation (NAT) technique resolved the IPv4 address shortage problem effectively. Meanwhile, it brings issues to network management. Unauthorized NAT devices may be a significant security problem. Attackers may conduct malicious activities by using computers hidden behind unauthorized NAT. The remote NAT detect algorithm is proposed based on support vector machine method. Different...
These years, P2P applications have multiplied, evolved and take a big part of Internet traffic workload. Identifying the P2P traffic and understanding their behavior is an important field. Some port, payload and transport layer feature based methods were proposed. P2P traffic identification methods by examining user payload or well-defined port numbers no longer adapt to current P2P applications....
A method to realize the P2P network traffic classification based on the SVM is proposed. This method uses the network traffic statistical characteristic and SVM method that based on the statistical theory to classifies the different P2P traffic application. Mainly research on four kind of network traffic classification, in document sharing BitTorrent, in media flows PPLive, in network telephone Skype,...
We propose a method of identifying anomalous traffic sources using flow statistics. We have investigated a way of detecting whether or not anomalies occur by observing the behavior of several time-series of flow statistics such as the number of flows. After detecting the occurrences of network anomalies, we need to identify the source of the anomalies. In this paper, we describe a method of identifying...
From weather to networks, forecasting techniques constitute an interesting challenge: rather than giving a faithful description of the current reality, as a looking glass would do, researchers seek crystal-ball models to speculate on the future. This work is the first to explore the use of support vector machines (SVM) for the purpose of link load forecast. SVMs work well in many learning situations,...
In this paper a non linear system identification problem is addressed. A support vector regressor is used to solve the Internet traffic identification problem. We give a basic idea underlying support vector (SV) machine for regression, which is a novel type of learning machine based on statistical learning theory. Furthermore, we describe how SV regressor can be applied for non linear system identification...
The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications over the past decade. Pattern recognition by learning the features in the training samples to classify the unknown flows is one of the main methods. However, many methods developed in the previous works are too complicated to...
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