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Peer-to-peer traffic detection technology based on DPI identification technology is a main technique for detecting Peer-to-peer traffic at present. Sampling strategy was used in which in order to improve the efficiency of the implementation. But how to set the optimal sampling fraction has not been a standard specification or method. This topic advanced the method how to determine the optimal sampling...
In this paper, an SVM (Support Vector Machines)-based P2P (Peer-to-peer) traffic identification algorithm is presented. It could capture traffic information online, training-offline and categories online. The SVM algorithm uses double characteristics IP and IP-Port to identify P2P traffic by means of different traffic features separately. From results of experiments, we proved that choosing the appropriate...
Peer-to-peer technology has become an extremely popular Internet application technology. This technology opens enormous business opportunities to the Internet and also seriously interferes with the quality of the Internet service. The traditional single deep flow inspection or deep packet inspection detection systems have owns merits and demerits. This paper describes a new peer-to-peer traffic identification...
Three classic multi-string matching algorithms such as AC, Wu-Manber and SBOM are researched and implemented in P2P traffic identification system based on Deep Packet Inspection in this paper. In order to adapt to the DPI technology, the code and parameter of these matching algorithm be make suitable adjustment. Three algorithms are used in DPI scanning under the same testing environment and the pretreatment...
DPI identification technology is a main technique of P2P data stream identification technology; the advantages of it are higher accuracy and the ability of distinguishing accurately which type of P2P applications. But it is difficult to apply in highspeed networks due to its slow execution speed. To solve this problem, this paper suggests six sampling strategies: invariable random sampling, invariable...
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