Full Text:   <444>

Summary:  <219>

CLC number: TN918.91

On-line Access: 2017-12-04

Received: 2017-03-23

Revision Accepted: 2017-08-09

Crosschecked: 2017-10-10

Cited: 0

Clicked: 2034

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Hui-fang Chen

http://orcid.org/0000-0002-1366-1030

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2017 Vol.18 No.10 P.1665-1676

http://doi.org/10.1631/FITEE.1700203


On detecting primary user emulation attack using channel impulse response in the cognitive radio network


Author(s):  Qiao-mu Jiang, Hui-fang Chen, Lei Xie, Kuang Wang

Affiliation(s):  College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   jiangqm@zju.edu.cn, chenhf@zju.edu.cn, xiel@zju.edu.cn, wangk@zju.edu.cn

Key Words:  Cognitive radio network, Primary user emulation attack, Subspace-based blind channel estimation, Channel impulse response


Qiao-mu Jiang, Hui-fang Chen, Lei Xie, Kuang Wang. On detecting primary user emulation attack using channel impulse response in the cognitive radio network[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(10): 1665-1676.

@article{title="On detecting primary user emulation attack using channel impulse response in the cognitive radio network",
author="Qiao-mu Jiang, Hui-fang Chen, Lei Xie, Kuang Wang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="18",
number="10",
pages="1665-1676",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700203"
}

%0 Journal Article
%T On detecting primary user emulation attack using channel impulse response in the cognitive radio network
%A Qiao-mu Jiang
%A Hui-fang Chen
%A Lei Xie
%A Kuang Wang
%J Frontiers of Information Technology & Electronic Engineering
%V 18
%N 10
%P 1665-1676
%@ 2095-9184
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700203

TY - JOUR
T1 - On detecting primary user emulation attack using channel impulse response in the cognitive radio network
A1 - Qiao-mu Jiang
A1 - Hui-fang Chen
A1 - Lei Xie
A1 - Kuang Wang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 18
IS - 10
SP - 1665
EP - 1676
%@ 2095-9184
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1700203


Abstract: 
Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service (DoS) attack, named the primary user emulation attack (PUEA), exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response (CIR) between the secondary user (SU) and the signal source is used to determine whether the received signal is transmitted by the primary user (PU) or the primary user emulator (PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.

认知无线电网络中利用信道冲击响应的主用户仿真攻击检测技术

概要:认知无线电通过将空闲频谱动态地分配给未授权用户,可以有效地解决频谱资源稀缺的问题。然而,在认知无线电网络中,存在着一种严重的拒绝服务攻击,称为"主用户仿真攻击",该攻击会导致认知无线电网络系统性能的下降。在本文中,我们提出了一种在认知无线电网络中利用无线信道信息进行主用户仿真攻击检测的方法。在该方法中,我们利用信号源与从用户之间信道冲激响应的独特性,判断从用户接收到的信号来源是主用户还是仿真主用户。我们进一步推导了所提出检测方法的虚警概率和检测概率的闭合表达式。另外,为使所提出的检测方法在从用户没有主用户信号结构和内容先验信息的场景下也能顺利工作,我们提出了一种改进的基于子空间的盲信道估计方法。仿真结果表明,即使主用户与仿真主用户到从用户之间信道冲激响应的差别较小,所提出的主用户仿真攻击检测方法也能取得较好的检测性能。

关键词:认知无线电网络;主用户仿真攻击;基于子空间的盲信道估计;信道冲击响应

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Chen, R.L., Park, J.M., 2006. Ensuring trustworthy spectrum sensing in cognitive radio networks. Proc. 1st IEEE Workshop on Networking Technologies for Software Defined Radio Networks, p.110-119.

[2]Chen, R.L., Park, J.M., Reed, J.H., 2008. Defense against primary user emulation attacks in cognitive radio networks. IEEE J. Sel. Areas Commun., 26(1):25-37.

[3]Chin, W.L., Le, T.N., Tseng, C.L., et al., 2014. Cooperative detection of primary user emulation attacks based on channel-tap power in mobile cognitive radio networks. Int. J. Ad Hoc Ubiq. Comput., 15(4):263-274.

[4]Fang, S.H., Chen, J.Y., Shieh, M.D., et al., 2013. Subspace-based blind channel estimation by separating real and imaginary symbols for cyclic-prefixed single-carrier systems. IEEE Trans. Broadcast., 59(4):698-704.

[5]Haykin, S., 2005. Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun., 23(2): 201-220.

[6]Jin, F., Varadharajan, V., Tupakula, U., 2015. Improved detection of primary user emulation attacks in cognitive radio networks. Proc. Int. Telecommunication Networks and Applications Conf., p.274-279.

[7]Jin, Z., Anand, S., Subbalakshmi, K.P., 2009. Mitigating primary user emulation attacks in dynamic spectrum access networks using hypothesis testing. ACM SIGMOBILE Mob. Comput. Commun. Rev., 13(2):74-85.

[8]Kay, S.M., 1993. Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice-Hall, New Jersey, p.27-82.

[9]Kim, J.G., Oh, J.H., Lim, J.T., 2012. Subspace-based channel estimation for MIMO-OFDM systems with few received blocks. IEEE Signal Process. Lett., 19(7):435-438.

[10]Lalos, A.S., Rontogiannis, A.A., Berberidis, K., 2010. Frequency domain channel estimation for cooperative communication networks. IEEE Trans. Signal Process., 58(6):3400-3405.

[11]Le, T.N., Chin, W.L., Kao, W.C., 2015. Cross-layer design for primary user emulation attacks detection in mobile cognitive radio networks. IEEE Commun. Lett., 19(5):799-802.

[12]Le, T.N., Chin, W.L., Lin, Y.H., 2016. Non-cooperative and cooperative PUEA detection using physical layer in mobile OFDM-based cognitive radio networks. Proc. Int. Conf. on Computing, Networking and Communications, p.1-5.

[13]Liu, M., Crussiere, M., Helard, J.F., 2012. A novel data-aided channel estimation with reduced complexity for TDS-OFDM systems. IEEE Trans. Broadcast., 58(2):247-260.

[14]Muquet, B., de Courville, M., Duhamel, P., 2002. Subspace-based blind and semi-blind channel estimation for OFDM systems. IEEE Trans. Signal Process., 50(7): 1699-1712.

[15]National Standard of the People’s Republic of China, 2007. Framing Structure, Channel Coding and Modulation for Digital Television Terrestrial Broadcasting System. GB 206000-2006 (in Chinese).

[16]Nguyen, N.T., Zheng, R., Han, Z., 2012. On identifying primary user emulation attacks in cognitive radio systems using nonparametric Bayesian classification. IEEE Trans. Signal Process., 60(3):1432-1445.

[17]Pu, D., Wyglinski, A.M., 2014. Primary-user emulation detection using database-assisted frequency-domain action recognition. IEEE Trans. Veh. Technol., 63(9):4372-4382.

[18]Rao, C.R., 1973. Linear Statistical Inference and Its Applications. John Wiley & Sons, New York, p.516-604.

[19]Su, B., Vaidyanathan, P.P., 2007. Subspace-based blind channel identification for cyclic prefix systems using few received blocks. IEEE Trans. Signal Process., 55(10): 4979-4993.

[20]Tomasoni, A., Gatti, D., Bellini, S., et al., 2013. Efficient OFDM channel estimation via an information criterion. IEEE Trans. Wirel. Commun., 12(3):1352-1362.

[21]Tugnait, J.K., Kim, H., 2010. A channel-based hypothesis testing approach to enhance user authentication in wireless networks. Proc. 2nd Int. Conf. on Communication Systems and Networks, p.1-9.

[22]Wooding, R.A., 1956. The multivariate distribution of complex normal variables. Biometrika, 43(1-2):212-215.

[23]Xin, C.S., Song, M., 2014. Detection of PUE attacks in cognitive radio networks based on signal activity pattern. IEEE Trans. Mob. Comput., 13(5):1022-1034.

[24]Zhou, W., Lam, W.H., 2010. Channel estimation and data detection for OFDM systems over fast-fading and dispersive channels. IEEE Trans. Veh. Technol., 59(3): 1381-1392.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE