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Application Type Identification of Internet Flows Based on Measure of Medium Truth Degree

Author: YangZheZuo
Tutor: ChengWeiQing
School: Nanjing University of Posts and Telecommunications
Course: Applied Computer Technology
Keywords: application type identification flow characteristics MMTD probability
CLC: TP393.06
Type: Master's thesis
Year: 2012
Downloads: 23
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Abstract


Internet application identification is required for a range of realms, such as network intrusion detection and QoS management. Nowadays new internet applications develop very fast and it makes application identification more difficult and important. Among main identification methods recently, port-based identification is able to be used in a smaller and smaller range, DPI method has a bad complexity of the algorithm, method basd on flow characteristics has a good complexity of the algorithm and scalability but it’s accuracy is not so good. Application identification requires further study.This paper aims to improve and perfect a novel approach of application type identification of internet flows related to Medium Mathematics, an application type identification method based on MMTD(Measure of Medium Truth Degree). The study showed that the original method has a well efficiency, scabability and good accuracy among all the flow characteristics based methods. But the parameters used in the method were probably based on network expertise and the experience of the artificial statistics and analysis of features of flows. The lack of systemic method of calculations of parameters affected the use and promotion of the identification method. This article improves and perfects the original method with machine learning technology and measure of probability in following aspects: (1)it proposes mappings between truth scales and metrics values that reflects the distribution characteristics of metrics of objects and the corresponding method of calculation of truth scales; (2)it proposes a method of metrics selection and a method of weights calculation based on intensity degrees of distribution characteristics of metrics; (3)it proposes a method that can calculate feature parameters of internet flow attributes by rigorous statictics and data processing methods; (4)it reveals the fuzzility of the method in this article, it uses the measure of fuzzility to improve the accuracy of formulas which calculate how a unknown flow is like a specific flow. (5)it uses the Measure of Probability to evaluate the validity of the whole method. The experimental result indicates the validity of the method of improvement and perfection proposed in this article. This thesis extends the Measure of Medium Truth Degree and proposed a method which is able to identify all the objects which have many characteristics.

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