| 一种基于神经网络与证据理论融合的P2P业务感知模型 |
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| 引用本文： | 顾成杰,张顺颐,黄河,孙雁飞.一种基于神经网络与证据理论融合的P2P业务感知模型[J].中国电子科学研究院学报,2010,5(2):148-151. |
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| 作者姓名： | 顾成杰 张顺颐 黄河 孙雁飞 |
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| 作者单位： | 1. 南京邮电大学,信息网络技术研究所,南京,210003
2. 北京航空航天大学,软件学院,北京,100083 |
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| 基金项目： | 国家高技术研究发展计划863资助项目(2009AA01Z212;2009AA01Z202) |
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| 摘 要： | 提出了一种基于神经网络与证据理论融合的P2P业务感知模型,该模型利用神经网络的非线性逼近能力和自学习能力,获取证据理论所需的基本概率值;并通过证据理论的数据融合明显提高业务感知准确率。实验结果表明,该模型与现行的P2P业务识别方法相比,能够快速、准确、可靠地识别P2P业务类别,实现合法有效的网络管理和控制,对检测网络异常行为与提高网络安全性具有重要意义。
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| 关 键 词： | 神经网络 证据理论 业务感知 P2P |
P2P Traffic Identification Model Based on Combination of Neural Networks with Evidence Theory |
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| GU Cheng-jie,ZHANG Shun-yi,HUANG He,SUN Yan-fei.P2P Traffic Identification Model Based on Combination of Neural Networks with Evidence Theory[J].Journal of China Academy of Electronics and Information Technology,2010,5(2):148-151. |
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| Authors: | GU Cheng-jie ZHANG Shun-yi HUANG He SUN Yan-fei |
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| Affiliation: | 1.Institute of Information Network Technology/a>;Nanjing University of Posts and Telecommunications/a>;Nanjing 210003/a>;China/a>;2.College of Software Beijing University of Aeronautics and Astronautics/a>;Beijing 100083/a>;China |
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| Abstract: | In order to improve the currently Internet traffic identification,we propose a novel P2P traffic identification model based on combination of neural networks with evidence theory.The model using neural networks nonlinear approximation ability and self-learning ability can be more objectively access to basic probability value required for evidence theory identification phrase,and improve greatly the Internet traffic identification accuracy after the re-integration of evidence theory.Contrasted with currently... |
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| Keywords: | neutral network evidence theory traffic identification P2P |
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