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International Journal of Distributed Sensor Networks

Secure performance analysis and detection of pilot attack in massive multiple-input multiple-output system

Xianyu Zhang, Daoxing Guo, Kefeng Guo, Hehao Niu

Published May 1, 2018• 9 citations
Publisher

Abstract

This article studies the physical layer security of massive multiple-input multiple-output system in time-division-duplex mode. Specifically, a single-cell downlink massive multiple-input multiple-output communication system is considered. The resulting achievable secrecy rate is investigated in the presence of passive or active eavesdroppers. The analytical results reveal that the massive multiple-input multiple-output system is naturally immune to passive eavesdroppers, but will be dramatically degraded by active attack. On account of the risk caused by active attack, a simple and effective detection algorithm is proposed. Uplink pilots with random phases are transmitted during the detection operation. By comparing the phase deviation change of the received pilot signals’ cross product, the active eavesdroppers can be detected exactly. The closed-form expressions for probabilities of detection, false alarm, and false rejection are obtained respectively, which can demonstrate the robust performance of the proposed detection scheme. To maximize the secrecy energy efficiency of the system, the optimal power allocation strategy is studied under total power constraints. This optimization problem is efficiently solved by fractional programming. Numerical simulation results are derived to validate the secrecy performance of the massive multiple-input multiple-output system, the active pilot attacker detection performance, and the energy efficiency optimization effect.

DOI
10.1177/1550147718776922

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This article studies the physical layer security of massive multiple-input multiple-output system in time-division-duplex mode. Specifically, a single-cell downlink massive multiple-input multiple-output communication system is considered. The resulting achievable secrecy rate is investigated in the presence of passive or active eavesdroppers. The analytical results reveal that the massive multiple-input multiple-output system is naturally immune to passive eavesdroppers, but will be dramatically degraded by active attack. On account of the risk caused by active attack, a simple and effective detection algorithm is proposed. Uplink pilots with random phases are transmitted during the detection operation. By comparing the phase deviation change of the received pilot signals’ cross product, the active eavesdroppers can be detected exactly. The closed-form expressions for probabilities of detection, false alarm, and false rejection are obtained respectively, which can demonstrate the robust performance of the proposed detection scheme. To maximize the secrecy energy efficiency of the system, the optimal power allocation strategy is studied under total power constraints. This optimization problem is efficiently solved by fractional programming. Numerical simulation results are derived to validate the secrecy performance of the massive multiple-input multiple-output system, the active pilot attacker detection performance, and the energy efficiency optimization effect.
In this paper, we investigate secure and reliable transmission strategies for multi-cell multi-user massive multiple-input multiple-output systems with a multi-antenna active eavesdropper. We consider a time-division duplex system where uplink training is required and an active eavesdropper can attack the training phase to cause pilot contamination at the transmitter. This forces the precoder used in the subsequent downlink transmission phase to implicitly beamform toward the eavesdropper, thus increasing its received signal power. Assuming matched filter precoding and artificial noise (AN) generation at the transmitter, we derive an asymptotic achievable secrecy rate when the number of transmit antennas approaches infinity. For the case of a single-antenna active eavesdropper, we obtain a closed-form expression for the optimal power allocation policy for the transmit signal and the AN, and find the minimum transmit power required to ensure reliable secure communication. Furthermore, we show that the transmit antenna correlation diversity of the intended users and the eavesdropper can be exploited in order to improve the secrecy rate. In fact, under certain orthogonality conditions of the channel covariance matrices, the secrecy rate loss introduced by the eavesdropper can be completely mitigated.
In this paper, we study the design of secure communication for time-division duplex multi-cell multi-user massive multiple-input-multiple-output (MIMO) systems with active eavesdropping. We assume that the eavesdropper actively attacks the uplink pilot transmission and the uplink data transmission before eavesdropping the downlink data transmission of the users. We exploit both the received pilot's and the received data signals for uplink channel estimation. We show analytically that when both the number of transmit antennas and the length of the data vector tend to infinity, the signals of the desired user and the eavesdropper lie in different eigenspaces of the received signal matrix at the base station, provided their signal powers are different. This finding reveals that decreasing (instead of increasing) the desired user's signal power might be an effective approach to combat a strong active attack from an eavesdropper. Inspired by this observation, we propose a data-aided secure downlink transmission scheme and derive an asymptotic achievable secrecy sum-rate expression for the proposed design. For the special case of a single-cell single-user system with independent and identically distributed fading, the obtained expression reveals that the secrecy rate scales logarithmically with the number of transmit antennas. This is the same scaling law as for the achievable rate of a single-user massive MIMO system in the absence of eavesdroppers. The numerical results indicate that the proposed scheme achieves significant secrecy rate gains compared with alternative approaches based on matched filter precoding with artificial noise generation and null space transmission.
In this paper, we study the design of secure communication for time division duplexing multi-cell multi-user massive multiple-input multiple-output (MIMO) systems with active eavesdropping. We assume that the eavesdropper actively attacks the uplink pilot transmission and the uplink data transmission before eavesdropping the downlink data transmission phase of the desired users. We exploit both the received pilots and data signals for uplink channel estimation. We show analytically that when the number of transmit antennas and the length of the data vector both tend to infinity, the signals of the desired user and the eavesdropper lie in different eigenspaces of the received signal matrix at the base station if their signal powers are different. This finding reveals that decreasing (instead of increasing) the desire user's signal power might be an effective approach to combat a strong active attack from an eavesdropper. Inspired by this result, we propose a data-aided secure downlink transmission scheme and derive an asymptotic achievable secrecy sum-rate expression for the proposed design. Numerical results indicate that under strong active attacks, the proposed design achieves significant secrecy rate gains compared to the conventional design employing matched filter precoding and artificial noise generation.
In this paper, we investigate secure and reliable transmission strategies for multi-cell multi-user massive multipleinput multiple-output (MIMO) systems in the presence of an active eavesdropper. We consider a time-division duplex system where uplink training is required and an active eavesdropper can attack the training phase to cause pilot contamination at the transmitter. This forces the precoder used in the subsequent downlink transmission phase to implicitly beamform towards the eavesdropper, thus increasing its received signal power. We derive an asymptotic achievable secrecy rate for matched filter precoding and artificial noise (AN) generation at the transmitter when the number of transmit antennas goes to infinity. For the achievability scheme at hand, we obtain the optimal power allocation policy for the transmit signal and the AN in closed form. For the case of correlated fading channels, we show that the impact of the active eavesdropper can be completely removed if the transmit correlation matrices of the users and the eavesdropper are orthogonal. Inspired by this result, we propose a precoder null space design exploiting the low rank property of the transmit correlation matrices of massive MIMO channels, which can significantly degrade the eavesdropping capabilities of the active eavesdropper.
In this article, the secure communication in cell-free massive multiple-input multiple-output system with low-resolution analog-to-digital converters is investigated in the presence of an active eavesdropper. Specifically, in this article, the deterioration caused by the analog-to-digital converter imperfections on the accuracy of the channel estimation and secure transmission performance is studied. Besides, the additive quantization noise model is utilized to analyze the impacts of the low-resolution analog-to-digital converters. The minimum mean square error channel estimation results show that there is a nonzero floor caused by the coarse analog-to-digital converters. Then, the closed-form expressions for both the legitimate users achievable ergodic rate and the information leakage to the eavesdropper are derived, respectively. Moreover, tight approximated ergodic secrecy rate expression is also presented with respect to analog-to-digital converters quantization bits, number of antennas, pilot power, and so on. To degrade the impacts of the pilot spoofing attack, an active attack detection approach based on random matrix theory is proposed which can only be operated at one access point. Simulation results are provided to corroborate the obtained results and analyze the impacts of various parameters on system secrecy performance. Also, the superiority of the proposed active attacks detection method is confirmed via simulation results.
In this article, downlink secure transmission in simultaneous information and power transfer (SWIPT) system enabled with massive multiple-input multiple-output (MIMO) is studied. A base station (BS) with a large number of antennas transmits energy and information signals to its intended users, but these signals are also received by an active eavesdropper. The users and eavesdropper employ a power splitting technique to simultaneously decode information and harvest energy. Massive MIMO helps the BS to focus energy to the users and prevent information leakage to the eavesdropper. The harvested energy by each user is employed for decoding information and transmitting uplink pilot signals for channel estimation. It is assumed that the active eavesdropper also harvests energy in the downlink and then contributes during the uplink training phase. Achievable secrecy rate is considered as the performance criterion and a closed-form lower bound for it is derived. To provide secure transmission, the achievable secrecy rate is then maximized through an optimization problem with constraints on the minimum harvested energy by the user and the maximum harvested energy by the eavesdropper. Numerical results show the effectiveness of using massive MIMO in providing physical layer security in SWIPT systems and also show that our closed-form expressions for the secrecy rate are accurate.