Packet Classification using Support Vector Machines with String Kernels

摘要

Since the inception of internet many methods have been devised to keep untrusted and malicious packets away from a user's system . The traffic / packet classification can be used as an important tool to detect intrusion in the system. Using Machine Learning as an efficient statistical based approach for classifying packets is a novel method in practice today . This paper emphasizes upon using an advanced string kernel method within a support vector machine to classify packets . There exists a paper related to a similar problem using Machine Learning [2]. But the researches mentioned in their paper are not up-to date and doesn't account for modern day string kernels that are much more efficient . My work extends their research by introducing different approaches to classify encrypted / unencrypted traffic / packets .