[1]顾成杰,张顺颐,杜安源.结合粗糙集和禁忌搜索的网络流量特征选择[J].智能系统学报,2011,6(3):254-260.
　GU Chengjie,ZHANG Shunyi,DU Anyuan.Feature selection of network traffic using a rough set and tabu search[J].CAAI Transactions on Intelligent Systems,2011,6(3):254-260.
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结合粗糙集和禁忌搜索的网络流量特征选择

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 6 期数: 2011年第3期 页码: 254-260 栏目: 学术论文—人工智能基础 出版日期: 2011-06-25
Title:
Feature selection of network traffic using a rough set and tabu search
文章编号:
1673-4785(2011)03-0254-07
作者:
顾成杰1,张顺颐1,杜安源2
1.南京邮电大学 信息网络技术研究所,江苏 南京 210003;
2.中国移动通信集团设计院有限公司 安徽分公司,安徽 合肥 230041
Author(s):
GU Chengjie1, ZHANG Shunyi1, DU Anyuan2
1.Institute of Information Network Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China；
2.Anhui Branch, China Mobile Group Design Institute, Hefei 230041, China
关键词:
粗糙集; 禁忌搜索; 特征选择; 网络流量
Keywords:
rough set;  tabu search;  feature selection;  network traffic
分类号:
TP391
文献标志码:
A
摘要:
针对网络流量特征属性的优化选择问题，提出了一种结合粗糙集和禁忌搜索的网络流量特征选择方法（RSTS）.该方法通过粗糙集算法对网络流量特征属性进行约简，将所得到的特征子集作为禁忌搜索的初始解，并利用禁忌搜索得到最优特征子集.实验验证RSTS方法优于基于GA的特征选择方法和基于IG的特征选择方法，能够有效地去除网络流量的冗余特征属性，提高网络流量分类精度.
Abstract:
A feature selection of network traffic using a rough set and tabu search (RSTS) was proposed for the purpose of optimization in the feature selection of traffic classification. This approach reduced the traffic feature attribute with a rough set and established the feature subset as the initial value of a tabu search, as well as the optimal feature subset on the basis of a tabu search. The optimal feature subset with a tabu search can be selected on the basis of a feature subset. In contrast with the traditional feature selection methods based on GA and IG, RSTS was validated optimal by experimental results. It can diminish redundant feature attribution of network traffic effectively and greatly improve the classification accuracy.
参考文献/References:
［1］NGUYEN T T, ARMITAGE G. A survey of techniques for internet traffic classification using machine learning［J］. IEEE Communications Surveys and Tutorials, 2008, 10(4): 5676.
［2］CALLADO A, KAMIENSKI C. A survey on internet traffic identification［J］. IEEE Communications Surveys and Tutorials, 2009, 11(3): 3752.
［3］ESTE A, GRINGOLI F, SALGARELLI L. Support vector machines for TCP traffic classification［J］. Computer Networks, 2009, 53(14): 24762490.
［4］POLAT K, GUNES S. A new feature selection method on classification of medical datasets: kernel Fscore feature selection［J］. Expert Systems with Applications, 2009, 36(7): 1036710373.
［5］PATRICIA E N, ENGELBRECHT A P. A decision rulebased method for feature selection in predictive data mining［J］. Expert Systems with Applications, 2010, 37(1): 602609.
［6］BARALDI P, PEDRONI N, ZIO E. Application of a nicked Pareto genetic algorithm for selecting features for nuclear transients classification［J］. International Journal of Intelligent Systems, 2009, 24(2): 118151.
［7］KIRA K, RENDELL L A. Feature selection problem: traditional methods and a new algorithm［C］//Proceedings of the Tenth National Conference on Artificial Intelligence. San Jose, USA, 1992: 129134.
［8］LI Yongming, ZHANG Sujuan, ZENG Xiaoping. Research of multipopulation agent genetic algorithm for feature selection［J］. Expert Systems with Applications, 2009, 36(7): 1157011581.
［9］HUANG Chenglung, DUN Jianfan. A distributed PSOSVM hybrid system with feature selection and parameter optimization［J］. Applied Soft Computing Journal, 2008, 8(4): 13811391.
［10］ZHANG Li, MENG Xiangru, WU Weijia, et al. Network fault feature selection based on adaptive immune clone selection algorithm［C］//Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization. Sanya, China, 2009: 969973.
［11］SWINIARSKI R W, SKOWRON A. Rough set methods in feature selection and recognition［J］. Pattern Recognition Letters, 2003, 24(6): 833849.
［12］殷志伟，张健沛.基于浓缩布尔矩阵的属性约简算法［J］.哈尔滨工程大学学报， 2009, 30(3)： 307311.
YIN Zhiwei, ZHANG Jianpei.An attribute reduction algorithm based on a concentration Boolean matrix［J］. Journal of Harbin Engineering University, 2009, 30(3): 307311.
［13］THANGAVEL K, PETHALAKSHMI A. Dimensionality reduction based on rough set theory: a review［J］. Applied Soft Computing Journal, 2009, 9(1): 112.
［14］WANG Yong, LI Lin, NI Jun, et al. Feature selection using tabu search with longterm memories and probabilistic neural networks［J］. Pattern Recognition Letters, 2009, 30(7): 661670.
［15］HEDAR A R, WANG J, FUKUSHIMA M. Tabu search〖LL〗for attribute reduction in rough set theory［J］. Soft Computing, 2008, 12(9): 909918.
［16］CHIOU Chiewun, WU Muhcheng. A GAtabu algorithm for scheduling inline steppers in lowyield scenarios［J］. Expert Systems with Applications, 2009, 36(9): 1192511933.
［17］MOORE A W, ZUEV D. Internet traffic classification using Bayesian analysis techniques［C］//International Conference on Measurement and Modeling of Computer Systems. New York, USA, 2005: 5060.
［18］YANG Y M, PEDERSEN J O. A comparative study on feature selection in text categorization［C］//Proceedings of the Fourteenth International Conference on Machine Learning. Nashville, USA, 1997: 412420.
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备注/Memo

收稿日期： 2010-08-28.
基金项目：国家“863”计划资助项目（2006AA01Z232,2009AA01Z212,2009AA01Z202）；江苏省自然科学基金资助项目（BK2007603）；江苏省高技术研究计划资助项目（BG2007045）；江苏省重大科技支撑计划资助项目（BE2008134）；江苏省科技成果转化专项基金资助项目（BA2007012）.
通信作者：顾成杰.E-mail：jackiee.gu@gmail.com.
作者简介：
顾成杰，男，1985年生，博士研究生，主要研究方向为通信网与IP技术、P2P网络、网络流量识别与认知网络.
?张顺颐，男，1944年生，教授，博士生导师，江苏省通信与网络工程技术研究中心主任，中国通信学会IP应用与增值电信业务专委会主任，中国电子学会通信学分会副主任.主要研究方向为计算机网络通信、下一代网络与IP技术、互联网络监测与管理.近年来先后主持完成国家“863”计划项目5项，国家科技支撑计划项目1项，江苏省重大科技成果产业化项目1项，江苏省高技术研究计划重点项目2项.获得省部级科技进步奖8项，完成专利申请30余项，发表学术论文100余篇.
杜安源，男，1979年生，工程师，主要研究方向为移动通信与无线资源管理、3G标准的应用性研究、移动通信技术设计与实施等.

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