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: 6583
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"
}
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%A Hui-fang Chen
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%J Frontiers of Information Technology & Electronic Engineering
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%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1700203
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T1 - On detecting primary user emulation attack using channel impulse response in the cognitive radio network
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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
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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.
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