认知无线电网络主用户模仿攻击下次用户通信性能分析

doi:10.3969/j.issn.1000-436x.2012.z2.013

通信学报 ›› 2012, Vol. 33 ›› Issue (Z2): 104-110.doi: 10.3969/j.issn.1000-436x.2012.z2.013

认知无线电网络主用户模仿攻击下次用户通信性能分析

王珊珊^1,²,罗兴国¹,李鹏³

¹ 国家数字交换系统工程技术研究中心，河南郑州 450000
² 解放军61580部队，北京 100000
³ 解放军95949部队，河北沧州 061000

出版日期:2012-11-25 发布日期:2017-08-03
基金资助:
国家高技术研究发展计划（“863”计划）基金资助项目;上海市科委重大科技攻关基金资助项目

Communication performance analysis of secondary users in cognitive radio networks under primary user emulation attacks

Shan-shan WANG^1,²,Xing-guo LUO¹,Peng LI³

¹ National Digital Switching System Engineering＆Technological R＆D Center,Zhengzhou 450000,China
² 61580 Troop,Beijing 100000,China
³ 95949 Troop,Cangzhou 061000,China

Online:2012-11-25 Published:2017-08-03
Supported by:
The National High Technology Research and Development Program of China(863 Program);The Committee of Science and Technology of Shanghai Municipality

摘要/Abstract

摘要：

随着认知无线电网络（CRN）技术的不断发展，安全问题日益受到重视。模仿主用户（PUE）是一种典型的易于实现且对CRN影响巨大的攻击行为，根据产生的原因、目的和过程的差异，可以分为恶意不端次用户PUE和自私不端次用户PUE 2类攻击。已有文献大多针对前者进行了分析，而对后者分析极少。重点对两者进行了区分，提出了四维连续时间马尔科夫链分析模型，详细地分析了自私不端次用户PUE攻击对正常次用户通信性能的影响，并对比了几类典型的PUE攻击检测技术。通过仿真结果可以看出：PUE攻击检测技术引入自私不端次用户检测机制极为必要，可以有效地改进检测效果。

关键词: 认知无线电网络, 频谱感知, 通信性能, 次用户, 仿冒主用户

Abstract:

Cognitive radio network(CRN)is an effective technology and a hot research direction which could solve the problem of deficient resource and revolutionize utilization.And its safety technology attracted more and more researches.Primary user emulation(PUE)is a typically easily and largely affecting attack.PUE attacked come from both malicious misbehavior secondary users(MMU)and selfish misbehavior secondary users(SMU).The former was studied much more deeply than the later one.Distinguishing MMU and SMU,a four dimensional continuous time markov chain model to analyze the communication performance of normal secondary users under PUE attacks,and typically affected by SMUs was proposed.Furthermore,several PUE detection technologies were compared.The emulation results indicate that the SMU detection mechanism is essential for the PUE attack detection technology,which can improve the detection effects largely.

Key words: cognition radio networks (CRN), spectrum sensing, communication performance, secondary user, primary user emulation(PUE)

王珊珊,罗兴国,李鹏. 认知无线电网络主用户模仿攻击下次用户通信性能分析[J]. 通信学报, 2012, 33(Z2): 104-110.

Shan-shan WANG,Xing-guo LUO,Peng LI. Communication performance analysis of secondary users in cognitive radio networks under primary user emulation attacks[J]. Journal on Communications, 2012, 33(Z2): 104-110.

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参考文献 11

[1]	MITOLA J , MAGUIRE G Q . Cognitive radio:making software radios more personal[J]. IEEE Personal Commun Mag, 1999,6(4): 13-18.
[2]	Federal Communications Commission . Notice of Proposed Rule Making and Order:Facilitating Opportunities for Flexible,Efficient,and Reliable Spectrum Use Employing Cognitive Radio Technologies[R]. ET Docket NO.03-108. 2005.
[3]	BALDO N , ASTERJADHI A , GIUPPONI L ,et al. A scalable dynamic spectrum access solution for large wireless networks[A]. ISWPC 5th IEEE International Symposium on Wireless Pervasive Computing[C]. Modena,Italy, 2010. 430-435.
[4]	BALDINI G , STURMAN T , BISWAS A ,et al. Security aspects in software defined radio and cognitive radio networks:a survey and a way ahead[J]. IEEE Communications Surveys ＆ Tutorials, 2011,14(2): 1-25.
[5]	JIN Z , ANAND S , SUBBALAKSHMI K P . Detecting primary user emulation attacks in dynamic spectrum access networks[A]. ICC IEEE International Conference on Communications[C]. Dresden,Germany, 2009. 1-5.
[6]	LIU Y , NING P , DAI H . Authenticating primary users’ signals in cognitive radio networks via integrated cryptographic and wireless link signatures[A]. IEEE Symposium on Security and Privacy(SP)[C]. San Francisco,USA, 2010. 286-301.
[7]	JIN Z , ANAND S , SUBBALAKSHMI K P . Performance analysis of dynamic spectrum access networks under primary user emulation attacks[A]. Proceedings of IEEE Globecom 2010[C]. Miami,USA, 2010. 1-5.
[8]	ANAND S , JIN Z , SUBBALAKSHMI K P . An analytical model for primary user emulation attacks in cognitive radio networks[A]. Proceedings IEEE DySPAN 2008[C]. Chicago,USA, 2008. 1-6.
[9]	JIN Z , ANAND S , SUBBALAKSHMI K . Detecting primary user emulation attacks in dynamic spectrum access networks[A]. IEEE International Conf Commun[C]. Dresden,Germany, 2009. 1-5.
[10]	WANG W K , LI H S , SUN Y ,et al. Research article securing collaborative spectrum sensing against untrustworthy secondary users in cognitive radio networks[J]. EURASIP Journal on Advances in Signal Processing, 2010,2010(2010): 1-15.
[11]	CHEN C , CHENG H B , YAO Y D . Cooperative spectrum sensing in cognitive radio networks in the presence of the primary user emulation attack[J]. IEEE Transactions on Wireless Communications, 2011,10(7): 2135-2141.

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认知无线电网络主用户模仿攻击下次用户通信性能分析

Communication performance analysis of secondary users in cognitive radio networks under primary user emulation attacks

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