本文選題：離散序列報(bào)文 + 協(xié)議關(guān)鍵字提取��； 參考：《計(jì)算機(jī)應(yīng)用》2017年04期

【摘要】：針對(duì)缺少會(huì)話信息的離散序列報(bào)文,提出一種基于離散序列報(bào)文的協(xié)議格式(SPMbFSC)特征自動(dòng)提取算法。SPMbFSC在對(duì)離散序列報(bào)文進(jìn)行聚類的基礎(chǔ)上,通過改進(jìn)的頻繁模式挖掘算法提取出協(xié)議關(guān)鍵字,進(jìn)一步對(duì)協(xié)議關(guān)鍵字進(jìn)行選擇,篩選出協(xié)議格式特征。仿真結(jié)果表明,SPMbFSC在以單個(gè)報(bào)文為顆粒度的識(shí)別中對(duì)FTP、HTTP等六種協(xié)議的識(shí)別率均能達(dá)到95%以上,在以會(huì)話為顆粒度的識(shí)別中識(shí)別率可達(dá)90%。同等實(shí)驗(yàn)條件下性能優(yōu)于自適應(yīng)特征(AdapSig)提取方法。實(shí)驗(yàn)結(jié)果表明SPMbFSC不依賴會(huì)話數(shù)據(jù)的完整性,更符合實(shí)際應(yīng)用中由于接收條件限制導(dǎo)致會(huì)話信息不完整的情形。
[Abstract]:In view of the lack of session information in discrete sequence packets, a protocol format named SPMbFSC based on discrete sequence packets is proposed. SPMbFSC is based on clustering discrete sequence packets.Through the improved frequent pattern mining algorithm, the protocol keywords are extracted, then the protocol keywords are selected, and the protocol format features are screened out.The simulation results show that SPMbFSC can recognize more than 95% of the six protocols, such as FTPU HTTP, in the recognition of single packet size, and the recognition rate can reach 90% in the case of session granularity recognition.Under the same experimental conditions, the performance is better than the adaptive characteristic Adapter Sigma extraction method.The experimental results show that SPMbFSC does not depend on the integrity of session data, and it is more suitable for the incomplete session information due to the limitation of reception conditions in practical applications.
【作者單位】： 信息工程大學(xué)信息系統(tǒng)工程學(xué)院;
【分類號(hào)】：TP393.06

【相似文獻(xiàn)】

相關(guān)期刊論文 前5條

1 霍凱;PC機(jī)與S7-200 PLC的通訊研究[J];中國(guó)儀器儀表;2005年04期

2 ;主編寄語[J];電信科學(xué);2002年03期

3 佟立飛;李龍華;;通用網(wǎng)關(guān)協(xié)議數(shù)據(jù)轉(zhuǎn)換軟件開發(fā)[J];自動(dòng)化技術(shù)與應(yīng)用;2012年01期

4 王超;肖偉;于秀青;普頓;;基于APM7101的漢、英雙語MP3導(dǎo)游機(jī)的設(shè)計(jì)與實(shí)現(xiàn)[J];電子設(shè)計(jì)工程;2010年11期

5 ;[J];;年期

相關(guān)碩士學(xué)位論文 前3條

1 孫芳慧;基于Net-Trace的未知協(xié)議格式逆向技術(shù)研究[D];哈爾濱工業(yè)大學(xué);2015年

2 成厚富;智能手機(jī)漏洞挖掘技術(shù)研究[D];西安電子科技大學(xué);2008年

3 吳小偉;基于動(dòng)態(tài)污點(diǎn)分析的網(wǎng)絡(luò)程序漏洞挖掘方法[D];華中科技大學(xué);2012年

，

本文編號(hào)：1762815