无线传感器网络入侵检测方法的研究
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摘要
随着无线传感器网络的快速发展及应用,在国防、环境监测、交通管理和森林保护等领域应用的越来越广泛,传感器网络的安全问题日益突出,而入侵检测是无线传感器网络安全研究的一个方面。因此,本文针对无线传感器网络及其入侵检测的特点进行研究,分析无线传感器网络入侵检测方法当前面临的主要问题。然后,针对主要问题研究了解决方法。
首先研究了无线传感器网络的特点；分别从物理层、数据链路层和网络层分别对无线传感器网络的入侵行为进行了详细的分析；并对三种典型的入侵检测模型进行了研究和对比。
其次从无线传感器网络面临的能耗问题和入侵检测性能问题出发,研究了一种基于分簇的无线传感器网络入侵检测模型,从节点信息采集、信息处理和入侵响应三个环节进行阐述,并针对能耗问题和入侵检测性能问题提出了相应的解决方案。
随后针对所研究的分簇无线传感网入侵检测模型进行了实验仿真和结果分析,对实验环境、实验方法和实验结果进行了详细的分析。本文实验中利用随机产生的入侵信号对无线传感器网络进行攻击,当入侵信号被接收端接收后,接收端会对接收到的信号进行分析。实验中是将有用的传输信号和入侵信号分别用不同的载波进行调制。在接收端再根据载波频率的不同来检测出入侵信号。最终,总结了论文的研究成果,阐明了将来的研究方向。本文的研究表明,无线传感器网络入侵检测方法的研究具有较好的实用价值。
With the rapid development and application of wireless sensor networks, applications in the field of national defense, environmental monitoring, traffic management and forest protection and a wide range of sensor network security issues have become increasingly prominent. Intrusion detection method for wireless sensor network security research is an important area. Study and propose a line sensor network intrusion detection method is very important in theoretical and practical significance.
First studied the characteristics of wireless sensor network; Respectively from the physical layer, data link layer and network layer, respectively, the invasion of the wireless sensor network behavior are analyzed in detail; And the three typical intrusion detection model is researched and compared.
Secondly from the energy consumption of wireless sensor network are faced with the problem and the intrusion detection performance problems, study a intrusion detection model based on clustering in wireless sensor network, from the node information collection, information processing and intrusion response expounds in three stages, and according to energy consumption problem and intrusion detection performance problems put forward the corresponding solutions. Then study the clustering wireless sensor network intrusion detection model are analyzed in simulation and experiment results, the experiment environment, experimental method and experimental results are analyzed.
The tests used in this article are randomly generated intrusion signal that attack the wireless sensor network, and after the intrusion signal received at the receiving end, the receiving end is interested in receiving the signal for analysis. Transmission signals and the intrusion signals are useful experiments, respectively, with a different carrier modulation. Depending on the carrier frequency to detect an intrusion signal at the receiving end.
Ultimately, a summary of the thesis research to clarify the direction of future research. This study showed that the wireless sensor network intrusion detection method has a good practical value.
首先研究了无线传感器网络的特点；分别从物理层、数据链路层和网络层分别对无线传感器网络的入侵行为进行了详细的分析；并对三种典型的入侵检测模型进行了研究和对比。
其次从无线传感器网络面临的能耗问题和入侵检测性能问题出发,研究了一种基于分簇的无线传感器网络入侵检测模型,从节点信息采集、信息处理和入侵响应三个环节进行阐述,并针对能耗问题和入侵检测性能问题提出了相应的解决方案。
随后针对所研究的分簇无线传感网入侵检测模型进行了实验仿真和结果分析,对实验环境、实验方法和实验结果进行了详细的分析。本文实验中利用随机产生的入侵信号对无线传感器网络进行攻击,当入侵信号被接收端接收后,接收端会对接收到的信号进行分析。实验中是将有用的传输信号和入侵信号分别用不同的载波进行调制。在接收端再根据载波频率的不同来检测出入侵信号。最终,总结了论文的研究成果,阐明了将来的研究方向。本文的研究表明,无线传感器网络入侵检测方法的研究具有较好的实用价值。
With the rapid development and application of wireless sensor networks, applications in the field of national defense, environmental monitoring, traffic management and forest protection and a wide range of sensor network security issues have become increasingly prominent. Intrusion detection method for wireless sensor network security research is an important area. Study and propose a line sensor network intrusion detection method is very important in theoretical and practical significance.
First studied the characteristics of wireless sensor network; Respectively from the physical layer, data link layer and network layer, respectively, the invasion of the wireless sensor network behavior are analyzed in detail; And the three typical intrusion detection model is researched and compared.
Secondly from the energy consumption of wireless sensor network are faced with the problem and the intrusion detection performance problems, study a intrusion detection model based on clustering in wireless sensor network, from the node information collection, information processing and intrusion response expounds in three stages, and according to energy consumption problem and intrusion detection performance problems put forward the corresponding solutions. Then study the clustering wireless sensor network intrusion detection model are analyzed in simulation and experiment results, the experiment environment, experimental method and experimental results are analyzed.
The tests used in this article are randomly generated intrusion signal that attack the wireless sensor network, and after the intrusion signal received at the receiving end, the receiving end is interested in receiving the signal for analysis. Transmission signals and the intrusion signals are useful experiments, respectively, with a different carrier modulation. Depending on the carrier frequency to detect an intrusion signal at the receiving end.
Ultimately, a summary of the thesis research to clarify the direction of future research. This study showed that the wireless sensor network intrusion detection method has a good practical value.
引文
[1]周贤伟,覃伯平,徐福华,无线传感器网络与安全,北京：国防工业出版社,2007.
[2]罗守山.入侵检测.北京邮电大学出版社,2004.
[3]Hong Nhung Thi Nguyen. Intrusion detection in WSNs. the degree of Master of Science in the School of Electrical Engineering and Computer Science in the College of Engineering and Computer Science at the University of Central Florida,2005.
[4]曾夏玲,梁艳招,彭雅丽,余敏.基于簇的无线传感器网络入侵检测系统.微电子学与计算机,2008,156-160.
[5]曾玲,黄益盛.无线传感器网络的安全保密技术研究田.信息安区与通信保密,2007(8)：83-88.
[6]林果园,黄皓,张永平.入侵检测系统研究进展[J].计算机科学,2008,35(2)：32-34
[7]周贤伟,覃伯平,徐福华.无线传感器网络与安全.国防工业出版社,2007：179-195
[8]W.T.Su, K.M.Chang, Y.H.Kuo. eHIP:An Energy-efficient hybrid intrusion prohibition system for cluster-based wireless sensor networks. Computer Networks.2007,51(4):1151-1168.
[9]S.S.Doumit, d.P.Agrawal. Self-organized criticality & stochastic learning based intrusion detection system for wireless sensor network.The 2003 IEEE Military Communications Conference, Boston, MA, USA,2003. Piscataway, NJ, USA, IEEE,2003:609-614.
[10]A.Agah, S.K.Das, K.Basu, M.Asadi:Intrusion detection in sensor networks:A non-cooperative game approach. Third IEEE International Symposium on Network Computing and Applications, Cambridge, MA, USA,2004. Los Alamitos, CA, USA, IEEE Computer. Soc,2004:343-346
[11]P.Techateerawat, A.Jennings:Energy Efficiency of Intrusion Detection Systems in Wireless Sensor Networks.2006 IEEE/WIC/ACM International Conference on Web Intelligence International Intelligence Agent Technology Workshops, Hong Kong, China,2006.Los Alamitos,CA,USA,IEEE Comput.Soc,2006:227-230.
[12]E.C.H.Ngai, J.C.Liu, M.R.Lyu. An efficient intruder detection algorithm against sinkhole attacks in wireless sensor networks. Computer Communications,2007, 30(11-12):2353-2364.
[13]B.Krishnamachari, S.Iyengar. Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks. IEEE Transactions on Computers,2004,53(3):241-250.
[14]I.Krontiris, T.Dimitriou, T.Giannetsos and M.Mpasoukos. Intrusion Detection of Sinkhole Attacks in Wireless Sensor Networks [C].Ireland:Lecture Notes in Computer Science,2008:150-161.
[15]王培,周贤伟,覃伯平,赵鹏,郑连存.基于多代理的无线传感器网络入侵检测系统研究.传感技术学报.2007,20(3)：677-681.
[16]刘阳.基于免疫原理的无线传感器网络入侵检测系统研究[D].北京：中国科学院计算技术研究所,2008.
[17]GJPotrie, W.J.Kaiser. Wileless integrated network sensors{C}. In communications of the ACM,2000.43(5):51-58.
[18]He H, Huang C, Blum B M.et al. Range-free localization schemes in large scale Sensor networks{C}.In:Proc of the 9th Annual Int Cof on Mobile Computing and Networking, San Diego, CA, UnitedStates,2003:81-95.
[19]邹肠,陈志刚.基于J-Sim的无线传感器网络拥塞攻击应对方法研究[J].南华大学学报(自然科学版),2009,23(1)：72-75.
[20]Halkes G P,Dam T V,and Langendoen K GComparing energy-saving MAC protocols for wireless sensor network s[J]. Mobile Networks and Applications, 2005,10(5):783-791.
[21]Cao Q,He T, and Fang L. Efficiency centric communication model for wireless sensor networks[A]. Proceedings of IEEE INFORCOM'06. Barcelona, Calalunya, Spain. May 2006:1-12.
[22]Anderson J P.Computer security thread monitoring and surveillance[R].Fort Washington,USA:James P Anderson Co,1980.
[23]Denning D E.An intrusion-detection model[J].IEEE Transactions on Software Engineering,1987,13(2):222-232.
[24]Ghosh A.,Schwartzhard A.A study using neural networks for anomaly and misuse detection[C].Washington DC:Proceedings of the USE2 NIX Security Symposium,1999,141-151.
[25]陈友,沈华伟,李洋,程学旗.一种高效的面向轻量级入侵检测系统的特征选择算法[J].计算机学报,2007,30(8)：1398-1408.
[26]姜立标,马乐,余建伟,刘永花.多阶段聚类—朴素贝叶斯的异常检测[J].重庆大学学报,2009,32(8)：983-986.
[27]宿娇娜,李巍,唐发根,李云春.基于NB分类方法的网络异常检测模型[J].计算机应用研究,2008,25(2)：569-571.
[28]田新广,段洣毅,程学旗.基于Shell命令和多重行为模式挖掘的用户伪装攻击检测.计算机学报,2010,33(4)：697-705.
[29]Pedro,PAZZANI M.On the optimality of the simple Bayesian classifier under zero-one loss[J].Machine Learning,1997,29(223):103-130.
[30]张义荣,削顺平,鲜明,王国玉.基于机器学习的入侵检测技术概述[J].计算机工程与应用,2006,44(2)：7-11.
[31]李涛.基于数据挖掘技术的自适应入侵检测系统模型[J].计算机工程与设计,2010,31(6)：1209-1229.
[32]彭竹苗.基于隐马尔可夫模型的入侵检测技术研究[D].无锡：江南大学.
[33]Y.Q.Zhang, W.Lee. Intrusion Detection in Wireless Ad-hoc Networks. The Sixth Annual International Conference on Mobile Computing and Networking, Boston, MA, USA,2000. New Youk, NY, USA, ACM,2000:275-283.
[34]A.Agah, S.k.Das, k.Basu, ete.Intrusion detection in sensor networks:A non-cooperative game approach{C}.Third IEEE International Symposium on Network Computing and Applicatio, Cambridge, MA, USA,2004.LosAlamitos, CA, USA, IEEEComputer,2004:343-346.
[35]A.P.R.Da Silva, A.A.F.Loureiro, M.H.T.Martins, L.B.Ruiz, B.P.S.Rocha, H.C.Wong. Decentralized intrusion detection in wireless sensor networks. Proceedings of the 1st ACM international workshop on Quality of service & security in wireless and mobile networks, Montreal, QB, Canada,2005. New York, USA, ACM,2005:16-23.
[36]郑国强,李建东,周志立.多跳无线传感器网络的高能效数据收集协议[J].软件学报,2010,21(9)：2320?2337.
[37]毛郁欣.基于多路径反馈的无线传感器网络安全数据收集方法[J].通信学报,2010,31(8A)：76-80.
[2]罗守山.入侵检测.北京邮电大学出版社,2004.
[3]Hong Nhung Thi Nguyen. Intrusion detection in WSNs. the degree of Master of Science in the School of Electrical Engineering and Computer Science in the College of Engineering and Computer Science at the University of Central Florida,2005.
[4]曾夏玲,梁艳招,彭雅丽,余敏.基于簇的无线传感器网络入侵检测系统.微电子学与计算机,2008,156-160.
[5]曾玲,黄益盛.无线传感器网络的安全保密技术研究田.信息安区与通信保密,2007(8)：83-88.
[6]林果园,黄皓,张永平.入侵检测系统研究进展[J].计算机科学,2008,35(2)：32-34
[7]周贤伟,覃伯平,徐福华.无线传感器网络与安全.国防工业出版社,2007：179-195
[8]W.T.Su, K.M.Chang, Y.H.Kuo. eHIP:An Energy-efficient hybrid intrusion prohibition system for cluster-based wireless sensor networks. Computer Networks.2007,51(4):1151-1168.
[9]S.S.Doumit, d.P.Agrawal. Self-organized criticality & stochastic learning based intrusion detection system for wireless sensor network.The 2003 IEEE Military Communications Conference, Boston, MA, USA,2003. Piscataway, NJ, USA, IEEE,2003:609-614.
[10]A.Agah, S.K.Das, K.Basu, M.Asadi:Intrusion detection in sensor networks:A non-cooperative game approach. Third IEEE International Symposium on Network Computing and Applications, Cambridge, MA, USA,2004. Los Alamitos, CA, USA, IEEE Computer. Soc,2004:343-346
[11]P.Techateerawat, A.Jennings:Energy Efficiency of Intrusion Detection Systems in Wireless Sensor Networks.2006 IEEE/WIC/ACM International Conference on Web Intelligence International Intelligence Agent Technology Workshops, Hong Kong, China,2006.Los Alamitos,CA,USA,IEEE Comput.Soc,2006:227-230.
[12]E.C.H.Ngai, J.C.Liu, M.R.Lyu. An efficient intruder detection algorithm against sinkhole attacks in wireless sensor networks. Computer Communications,2007, 30(11-12):2353-2364.
[13]B.Krishnamachari, S.Iyengar. Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks. IEEE Transactions on Computers,2004,53(3):241-250.
[14]I.Krontiris, T.Dimitriou, T.Giannetsos and M.Mpasoukos. Intrusion Detection of Sinkhole Attacks in Wireless Sensor Networks [C].Ireland:Lecture Notes in Computer Science,2008:150-161.
[15]王培,周贤伟,覃伯平,赵鹏,郑连存.基于多代理的无线传感器网络入侵检测系统研究.传感技术学报.2007,20(3)：677-681.
[16]刘阳.基于免疫原理的无线传感器网络入侵检测系统研究[D].北京：中国科学院计算技术研究所,2008.
[17]GJPotrie, W.J.Kaiser. Wileless integrated network sensors{C}. In communications of the ACM,2000.43(5):51-58.
[18]He H, Huang C, Blum B M.et al. Range-free localization schemes in large scale Sensor networks{C}.In:Proc of the 9th Annual Int Cof on Mobile Computing and Networking, San Diego, CA, UnitedStates,2003:81-95.
[19]邹肠,陈志刚.基于J-Sim的无线传感器网络拥塞攻击应对方法研究[J].南华大学学报(自然科学版),2009,23(1)：72-75.
[20]Halkes G P,Dam T V,and Langendoen K GComparing energy-saving MAC protocols for wireless sensor network s[J]. Mobile Networks and Applications, 2005,10(5):783-791.
[21]Cao Q,He T, and Fang L. Efficiency centric communication model for wireless sensor networks[A]. Proceedings of IEEE INFORCOM'06. Barcelona, Calalunya, Spain. May 2006:1-12.
[22]Anderson J P.Computer security thread monitoring and surveillance[R].Fort Washington,USA:James P Anderson Co,1980.
[23]Denning D E.An intrusion-detection model[J].IEEE Transactions on Software Engineering,1987,13(2):222-232.
[24]Ghosh A.,Schwartzhard A.A study using neural networks for anomaly and misuse detection[C].Washington DC:Proceedings of the USE2 NIX Security Symposium,1999,141-151.
[25]陈友,沈华伟,李洋,程学旗.一种高效的面向轻量级入侵检测系统的特征选择算法[J].计算机学报,2007,30(8)：1398-1408.
[26]姜立标,马乐,余建伟,刘永花.多阶段聚类—朴素贝叶斯的异常检测[J].重庆大学学报,2009,32(8)：983-986.
[27]宿娇娜,李巍,唐发根,李云春.基于NB分类方法的网络异常检测模型[J].计算机应用研究,2008,25(2)：569-571.
[28]田新广,段洣毅,程学旗.基于Shell命令和多重行为模式挖掘的用户伪装攻击检测.计算机学报,2010,33(4)：697-705.
[29]Pedro,PAZZANI M.On the optimality of the simple Bayesian classifier under zero-one loss[J].Machine Learning,1997,29(223):103-130.
[30]张义荣,削顺平,鲜明,王国玉.基于机器学习的入侵检测技术概述[J].计算机工程与应用,2006,44(2)：7-11.
[31]李涛.基于数据挖掘技术的自适应入侵检测系统模型[J].计算机工程与设计,2010,31(6)：1209-1229.
[32]彭竹苗.基于隐马尔可夫模型的入侵检测技术研究[D].无锡：江南大学.
[33]Y.Q.Zhang, W.Lee. Intrusion Detection in Wireless Ad-hoc Networks. The Sixth Annual International Conference on Mobile Computing and Networking, Boston, MA, USA,2000. New Youk, NY, USA, ACM,2000:275-283.
[34]A.Agah, S.k.Das, k.Basu, ete.Intrusion detection in sensor networks:A non-cooperative game approach{C}.Third IEEE International Symposium on Network Computing and Applicatio, Cambridge, MA, USA,2004.LosAlamitos, CA, USA, IEEEComputer,2004:343-346.
[35]A.P.R.Da Silva, A.A.F.Loureiro, M.H.T.Martins, L.B.Ruiz, B.P.S.Rocha, H.C.Wong. Decentralized intrusion detection in wireless sensor networks. Proceedings of the 1st ACM international workshop on Quality of service & security in wireless and mobile networks, Montreal, QB, Canada,2005. New York, USA, ACM,2005:16-23.
[36]郑国强,李建东,周志立.多跳无线传感器网络的高能效数据收集协议[J].软件学报,2010,21(9)：2320?2337.
[37]毛郁欣.基于多路径反馈的无线传感器网络安全数据收集方法[J].通信学报,2010,31(8A)：76-80.