| 手机流量非侵入式监测的决策树算法 |
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| 引用本文： | 易军凯,李正东,李辉.手机流量非侵入式监测的决策树算法[J].计算机科学,2016,43(Z6):361-364. |
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| 作者姓名： | 易军凯 李正东 李辉 |
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| 作者单位： | 北京化工大学信息科学与技术学院 北京100029,北京化工大学信息科学与技术学院 北京100029,北京化工大学信息科学与技术学院 北京100029 |
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| 基金项目： | 本文受北京化工大学学科建设项目基金(XK1520)资助 |
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| 摘 要： | 针对现有手机中不良软件难以监测和识别的问题,提出并实现了手机流量监测系统,采用非侵入式方法获取手机流量数据,根据特征采用ID3算法建立决策树模型,再根据此决策树规则对流量数据进行分类。实验结果表明:该方法对手机流量类型的识别准确率在92%以上。
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| 关 键 词： | 流量监测 决策树 流量特征 ID3算法 |
Decision Tree Algorithm in Non-invasive Monitoring Cell Phone Traffic |
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| YI Jun-kai,LI Zheng-dong and LI Hui.Decision Tree Algorithm in Non-invasive Monitoring Cell Phone Traffic[J].Computer Science,2016,43(Z6):361-364. |
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| Authors: | YI Jun-kai LI Zheng-dong and LI Hui |
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| Affiliation: | College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China,College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China and College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China |
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| Abstract: | The purpose of this paper is to solve the problem that it is difficult to monitor and identify the malicious software in the cell phone.Aiming at proposing and realizing a mobile traffic monitoring system,we used non-invasive method to get phone traffic data.A decision tree model was established using the ID3 algorithm for the data,and then the traffic data was classified according to the decision tree rule.The experiment results show that the method can identify the traffic flow generated by the cell phone and the recognition accuracy rate can reach more than 92%. |
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| Keywords: | Traffic monitoring Decision tree Traffic features ID3 algorithm |
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