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In this paper, we apply nonlinear support vector machines to identify peer-to-peer (p2p) traffic in high-performance routers with packet sampling. Due to their high port rates, those routers cannot extract the headers of all the packets that traverse them, but only a sample. The results in this paper suggest that nonlinear support vector machines are highly successful and outperform recent approaches like [1,2].

Support Vector Machine Detection of Peer-to-Peer Traffic in High-Performance Routers with Packet Sampling: Nonlinear Kernel Approach