Abstract
Pilot spoofing attack (PSA) is a kind of active eavesdropping, which launches the identical training sequence to manipulate the channel estimation outcome during the pilot training phase. The newly proposed intelligent reflecting surface (IRS) system is vulnerable to the PSA because it relies on the pilot-assisted channel estimation methods to obtain channel statement information (CSI). To combat PSA in IRS-assisted systems, we consider two significant challenges: 1) channel distribution information (CDI) is uncertain, which will make the PSA detection methods based on the statistic feature (SF) invalid; 2) the noise is uncertain when detecting PSA in practical scenarios, which would impair the popular energy-based detectors. In this paper, we design a three-step training (TST) scheme. The effective detector could achieve reliable detection performance by examining the transmitter's received signal power levels when PSA occurs. The proposed method does not require the prior knowledge of noise variance and could obtain the CSI of both legitimate and illegitimate dyadic backscatter channels. Theoretical analysis and numerical simulations are presented further to demonstrate the efficiency of our proposed TST scheme.
Highlights
Security has been one of the critical considerations in wireless communications
We propose a three-step training (TST) scheme, which includes two sections: first, Alice and Bob conduct the two-way training, in which the legitimate dyadic backscatter channel (Alice-Bob) and illegitimate dyadic backscatter channel (Alice-Eve) can be accurately obtained; second, Bob conducts the uplink training, Alice applies the maximum-ratio combining (MRC) to capture the spoofing pilot signal and calculate the maximum likelihood estimation (MLE) of it’s power
In order to analyze the detection performance of the TST scheme under noise uncertainty, we introduce the worstcase performance of the detection (WCPD) scheme for comparison
Summary
Security has been one of the critical considerations in wireless communications. Due to the open transmission nature of the wireless medium, wireless devices are vulnerable to illegal eavesdropping of malicious users. Two meaningful challenges are taken into account: 1) The CDI is uncertain, which would deteriorate the performance of SF-based detectors; 2) the noise is uncertain when detecting PSA in a practical scenario, which would impair the threshold process To address these problems, we propose a three-step training (TST) scheme, which includes two sections: first, Alice and Bob conduct the two-way training, in which the legitimate dyadic backscatter channel (Alice-Bob) and illegitimate dyadic backscatter channel (Alice-Eve) can be accurately obtained; second, Bob conducts the uplink training, Alice applies the maximum-ratio combining (MRC) to capture the spoofing pilot signal and calculate the maximum likelihood estimation (MLE) of it’s power. N (0, σ 2) denotes the distribution of circular symmetric Gaussian (CSCG) random variable whose mean and variance are 0 and σ 2, respectively
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