WF-C4.5:WiFi環(huán)境下基于C4.5決策樹的手持終端流量識別方法
發(fā)布時(shí)間：2018-11-06 12:40
【摘要】：目前移動數(shù)據(jù)流量已占全球IP流量的47%,其中WiFi流量已占整個移動數(shù)據(jù)流量的90%以上。WiFi環(huán)境下移動終端流量的識別對互聯(lián)網(wǎng)流量管理具有重要意義。傳統(tǒng)基于HTTP用戶代理(User Agent,UA)的流量識別方法存在識別率不高的問題。分析了WiFi環(huán)境下移動終端連接持續(xù)時(shí)間、數(shù)據(jù)包大小、有效載荷大小等流量特征,提出一種WiFi環(huán)境下基于C4.5決策樹的手持終端設(shè)備流量識別方法 WF-C4.5,通過計(jì)算各屬性值的信息增益率構(gòu)建決策樹模型,實(shí)現(xiàn)手持終端與非手持終端流量的區(qū)分。實(shí)驗(yàn)表明,相比UA方法65%的準(zhǔn)確率,所提方法的準(zhǔn)確率高達(dá)95%。
[Abstract]:At present, mobile data traffic has accounted for 47% of global IP traffic, of which WiFi traffic has accounted for more than 90% of the total mobile data traffic. The identification of mobile terminal traffic in WiFi environment is of great significance to Internet traffic management. The traditional traffic identification method based on HTTP user Agent (User Agent,UA) has the problem of low recognition rate. This paper analyzes the flow characteristics of mobile terminal connection duration, packet size and payload in WiFi environment, and proposes a mobile terminal traffic identification method WF-C4.5, based on C4.5 decision tree in WiFi environment. By calculating the information gain rate of each attribute value, a decision tree model is constructed to distinguish the traffic between the handheld terminal and the non-handheld terminal. The experimental results show that the accuracy of the proposed method is as high as 95% compared with the 65% accuracy of the UA method.
【作者單位】： 湖北大學(xué)計(jì)算機(jī)與信息工程學(xué)院;湖北省教育信息化工程技術(shù)研究中心;
【基金】：賽爾網(wǎng)絡(luò)下一代互聯(lián)網(wǎng)技術(shù)創(chuàng)新項(xiàng)目(NGII20150101)資助
【分類號】：TN92;TP393.06
，
本文編號：2314298
[Abstract]:At present, mobile data traffic has accounted for 47% of global IP traffic, of which WiFi traffic has accounted for more than 90% of the total mobile data traffic. The identification of mobile terminal traffic in WiFi environment is of great significance to Internet traffic management. The traditional traffic identification method based on HTTP user Agent (User Agent,UA) has the problem of low recognition rate. This paper analyzes the flow characteristics of mobile terminal connection duration, packet size and payload in WiFi environment, and proposes a mobile terminal traffic identification method WF-C4.5, based on C4.5 decision tree in WiFi environment. By calculating the information gain rate of each attribute value, a decision tree model is constructed to distinguish the traffic between the handheld terminal and the non-handheld terminal. The experimental results show that the accuracy of the proposed method is as high as 95% compared with the 65% accuracy of the UA method.
【作者單位】： 湖北大學(xué)計(jì)算機(jī)與信息工程學(xué)院;湖北省教育信息化工程技術(shù)研究中心;
【基金】：賽爾網(wǎng)絡(luò)下一代互聯(lián)網(wǎng)技術(shù)創(chuàng)新項(xiàng)目(NGII20150101)資助
【分類號】：TN92;TP393.06
，
本文編號：2314298
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