本文選題：網絡流量分類 + 分類器評價　； 參考：《北京郵電大學》2014年碩士論文

【摘要】：近幾年,互聯(lián)網基礎建設和內容服務均快速發(fā)展,隨之帶動了互聯(lián)網寬帶業(yè)務的發(fā)展。據我國互聯(lián)網信息中心CNNIC測算,截至2013年6月底,我國網民規(guī)模達5.91億,互聯(lián)網普及率為44.1%。產生網絡流量的根本原因是互聯(lián)網中的網絡應用。實現(xiàn)網絡流量的正確識別并分析網絡流量的特征,是我們深入理解網絡狀況,用戶行為,互聯(lián)網現(xiàn)狀的前提條件,無論是對網絡管理員還是對用戶和服務提供商,都具有重要的意義。 網絡流量分類技術,是分析網絡流量特征和增強網絡可控性的基本手段之一,廣泛運用于流量監(jiān)控、網絡安全檢測、用戶行為分析、計費管理或其他網絡活動中。在對固定互聯(lián)網的特征進行分析研究的同時,隨著移動互聯(lián)網的迅猛發(fā)展,對移動互聯(lián)網流量的特征分析也顯得尤為重要。不僅用戶數(shù)量激增,同時隨著線速越來越高,網絡流量越來越大,在線的商用設備每天都能產生TB級甚至更龐大的流量數(shù)據。網絡流量已呈現(xiàn)大數(shù)據特征,對海量數(shù)據的存儲和分析已成為網絡流量特征分析的重要研究內容。 為了方便對網絡流量進行分析,我們開發(fā)了網絡流量分類與分類系統(tǒng)(Traffic Analysis and Classification System, TACS)以及海量數(shù)據分析系統(tǒng)LogAnalyser。本文首先介紹網絡流量分類及分析方法,在簡要介紹TACS系統(tǒng)之后,對網絡流量分類中分類器評價標準進行了深入研究。在此基礎上,本文對真實的網絡數(shù)據進行了基于DFI(Deep Flow Inspection)的流量分類并對已有分類器評價標準進行了改進。針對海量網絡流量數(shù)據的分析,整體介紹了自主開發(fā)的分析系統(tǒng)。最后,依據TACS和LogAnalyser,本文對固定互聯(lián)網和移動互聯(lián)網的網絡流量數(shù)據進行了不同角度的流量特征分析。
[Abstract]:In recent years, Internet infrastructure and content services have developed rapidly, which has led to the development of Internet broadband services. According to CNNIC, China's Internet Information Center, by the end of June, 2013, the number of Internet users in China reached 591 million, and the Internet penetration rate was 44.1%. The fundamental reason for the network traffic is the network application in the Internet. Realizing the correct identification of network traffic and analyzing the characteristics of network traffic is a prerequisite for us to deeply understand the network situation, user behavior, and the current situation of the Internet, whether for network administrators or users and service providers. Are of great significance. Network traffic classification technology is one of the basic methods to analyze network traffic characteristics and enhance network controllability. It is widely used in traffic monitoring, network security detection, user behavior analysis, billing management and other network activities. At the same time, with the rapid development of mobile Internet, it is particularly important to analyze the characteristics of mobile Internet traffic. Not only does the number of users surge, but also as the speed of the line increases and the network traffic becomes larger and larger, online commercial devices can generate terabytes or even larger traffic data every day. Network traffic has been characterized by big data, and the storage and analysis of massive data has become an important research content of network traffic feature analysis. In order to facilitate the analysis of network traffic, we have developed Traffic Analysis and Classification System, TACS), a network traffic classification and classification system, and LogAnalyser. a massive data analysis system. This paper first introduces the classification and analysis method of network traffic. After a brief introduction of TACS system, the evaluation standard of classifier in network traffic classification is studied deeply. On this basis, this paper classifies the real network data based on DFI(Deep Flow inspection and improves the evaluation criteria of existing classifiers. Based on the analysis of massive network traffic data, this paper introduces the analysis system developed by ourselves. Finally, according to TACS and Log Analyser, this paper analyzes the traffic characteristics of fixed and mobile Internet traffic data from different angles.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.06

【參考文獻】

相關期刊論文 前7條

1 林平;余循宜;劉芳;雷振明;;基于流統(tǒng)計特性的網絡流量分類算法[J];北京郵電大學學報;2008年02期

2 秦鋒;羅慧;程澤凱;任詩流;;一種新的基于AUC的多類分類評估方法[J];計算機工程與應用;2008年05期

3 王變琴;余順爭;;基于機器學習的網絡應用識別研究[J];計算機科學;2009年01期

4 倪黃晶;王蔚;;多類不平衡數(shù)據上的分類器性能比較研究[J];計算機工程;2011年10期

5 畢春光;陳桂芬;;基于數(shù)據挖掘的貝葉斯算法應用研究[J];農業(yè)網絡信息;2010年03期

6 劉穎秋;李巍;李云春;;網絡流量分類與應用識別的研究[J];計算機應用研究;2008年05期

7 秦鋒;楊波;程澤凱;;分類器性能評價標準研究[J];計算機技術與發(fā)展;2006年10期

，

本文編號：1952963