【摘要】：隨著社會(huì)生活的不斷網(wǎng)絡(luò)化,網(wǎng)絡(luò)應(yīng)用從基于客戶端／服務(wù)器(C/S)和瀏覽器／服務(wù)器(B/s)結(jié)構(gòu)的傳統(tǒng)業(yè)務(wù)逐漸轉(zhuǎn)向基于對(duì)等網(wǎng)絡(luò)P2P結(jié)構(gòu)的網(wǎng)絡(luò)應(yīng)用。大量基于P2P網(wǎng)絡(luò)結(jié)構(gòu)的P2P流量給互聯(lián)網(wǎng)環(huán)境帶來(lái)了諸多問(wèn)題,如網(wǎng)絡(luò)流量激增造成帶寬擁擠和網(wǎng)絡(luò)信息良莠不齊等。研究管理和控制P2P流量對(duì)避免網(wǎng)絡(luò)擁堵、限制非法流量和凈化網(wǎng)絡(luò)環(huán)境等具有非常重要的現(xiàn)實(shí)意義。本文圍繞網(wǎng)絡(luò)管理和控制的關(guān)鍵技術(shù)問(wèn)題：網(wǎng)絡(luò)流量檢測(cè)技術(shù)和模式匹配算法展開(kāi)深入研究,建立了流量監(jiān)控系統(tǒng)的協(xié)議特征庫(kù),并設(shè)計(jì)實(shí)現(xiàn)了流量檢測(cè)模塊和特征庫(kù)維護(hù)模塊。本文的主要工作體現(xiàn)在以下幾個(gè)方面： 1、重點(diǎn)研究了深度包檢測(cè)DPI、深度流檢測(cè)DFI和深層解析關(guān)聯(lián)匹配三種流量檢測(cè)技術(shù)。用該三種流量檢測(cè)技術(shù)提取了三十種網(wǎng)絡(luò)應(yīng)用(包括QQ、優(yōu)酷和迅雷等)的協(xié)議特征,并建立相應(yīng)的協(xié)議特征庫(kù)。 2、設(shè)計(jì)并實(shí)現(xiàn)了流量監(jiān)控系統(tǒng)中的流量檢測(cè)模塊。提出對(duì)網(wǎng)絡(luò)電話VoIP流量采用深層解析關(guān)聯(lián)匹配方法檢測(cè)。采用AC BM字符串匹配算法將未知流量與協(xié)議特征庫(kù)匹配,實(shí)現(xiàn)對(duì)未知流量分類。 3、設(shè)計(jì)并實(shí)現(xiàn)了流量監(jiān)控系統(tǒng)中的特征庫(kù)維護(hù)模塊。該模塊用于檢測(cè)并記錄網(wǎng)絡(luò)應(yīng)用版本是否升級(jí),其檢測(cè)結(jié)果結(jié)合現(xiàn)網(wǎng)流量變化為是否刷新特征庫(kù)提供依據(jù)。 4、在協(xié)議特征庫(kù)、流量檢測(cè)模塊和特征庫(kù)維護(hù)模塊功能測(cè)試成功的基礎(chǔ)上進(jìn)行流量監(jiān)控系統(tǒng)整體測(cè)試,結(jié)果表明該流量監(jiān)控系統(tǒng)具有較高的流量分類準(zhǔn)確率和較好的流量控制能力。
[Abstract]:With the continuous networking of social life, network applications have gradually changed from traditional services based on client / server (C / S) and browser / server (B / S) structures to P2P applications based on peer-to-peer networks. A large number of P2P traffic based on P2P network structure has brought many problems to the Internet environment, such as the congestion of bandwidth caused by the surge of network traffic and the intermingling of network information and so on. It is very important to study the management and control of P2P traffic in order to avoid network congestion, limit illegal traffic and purify network environment. This paper focuses on the key technical problems of network management and control: network traffic detection technology and pattern matching algorithm, and establishes the protocol signature database of traffic monitoring system. And designed and implemented the flow detection module and feature database maintenance module. The main work of this paper is as follows: 1. Three flow detection techniques, depth packet detection (DPI,) and deep correlation matching (DFI), are studied in detail. The protocol features of 30 network applications (including QQ, Youku and Thunder) are extracted by these three traffic detection techniques, and the corresponding protocol signature library is established. 2. The flow detection module in the flow monitoring system is designed and implemented. In this paper, the deep analytic association matching method is used to detect the VoIP traffic of network telephone. AC BM string matching algorithm is used to match unknown traffic and protocol signature database. 3. 3. The feature database maintenance module in traffic monitoring system is designed and implemented. The module is used to detect and record whether the network application version is upgraded or not, and its detection results combined with the current network traffic changes to provide a basis for whether to refresh the signature library. On the basis of the successful function testing of the flow detection module and the feature database maintenance module, the overall flow monitoring system is tested. The results show that the flow monitoring system has higher flow classification accuracy and better flow control ability.
【學(xué)位授予單位】：西北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.06

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