A Peer to Peer Traffic Identification Method Using K-Means Clustering, SVM & Genetic Algorithm
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 5
Abstract
the utilization of shared (p2p) applications is developing significantly, which brings about a few major issues, for example, the system clog and traffic obstruction. Consequently p2p traffic identification is the most blazing theme of p2p traffic administration. Support vector machine (svm) has points of interest with settling little examples for p2p characterization issues. However, the execution of svm is basically reliant on its parameters. In this paper we propose genetic algorithm and k-means with svm to streamline the parameters of svm and have been connected to p2p traffic identification. The curiosity of the proposed strategy is that it uses just the extent of parcels traded between ips inside seconds. The recognized components of the proposed technique lie in that quick calculation, high identification precision, and asset sparing capacity. At last, experiment results demonstrate the satisfactory performance of the proposed method.
Authors and Affiliations
Puja Raghav, Dr. Vivek Jaglan, Mr. Akshat Aggarwal
Keywords
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