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International Conference on Communications

Channel training design in full-duplex wiretap channels to enhance physical layer security

Shihao Yan, Xiangyun Zhou, Nan Yang, Thushara Dheemantha Abhayapala, Arnold Lee Swindlehurst

Published May 1, 2017• 11 citations
Publisher

Abstract

In this work, we propose a new channel training (CT) scheme to enhance physical layer security in a full-duplex wiretap channel, where the multi-antenna and full-duplex receiver simultaneously receives the information signal and transmits artificial noise (AN). In order to suppress the self-interference caused by AN, the receiver has to estimate the self-interference channel prior to the data communication phase. In the proposed CT scheme, the receiver transmits limited pilot symbols which are known only to itself, which prevents the eavesdropper from estimating the jamming channel from the receiver to the eavesdropper, hence effectively degrades the eavesdropping capability. Compared with the traditional CT scheme that uses publicly known pilots, the newly proposed secret CT scheme offers significantly better performance when the number of antennas at the eavesdropper is larger than one, e.g., Ne> 1. The optimal power allocation between CT and data/AN transmission at the legitimate transmitter/receiver is determined for the proposed secret CT scheme.

DOI
10.1109/icc.2017.7996663

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In this work, we propose a new channel training (CT) scheme to enhance physical layer security in a full-duplex wiretap channel, where the multi-antenna and full-duplex receiver simultaneously receives the information signal and transmits artificial noise (AN). In order to suppress the self-interference caused by AN, the receiver has to estimate the self-interference channel prior to the data communication phase. In the proposed CT scheme, the receiver transmits limited pilot symbols which are known only to itself, which prevents the eavesdropper from estimating the jamming channel from the receiver to the eavesdropper, hence effectively degrades the eavesdropping capability. Compared with the traditional CT scheme that uses publicly known pilots, the newly proposed secret CT scheme offers significantly better performance when the number of antennas at the eavesdropper is larger than one, e.g., Ne> 1. The optimal power allocation between CT and data/AN transmission at the legitimate transmitter/receiver is determined for the proposed secret CT scheme.
This paper proposes a new channel training (CT) scheme for a full-duplex receiver to enhance physical layer security. Equipped with NBfull-duplex antennas, the receiver simultaneously receives the information signal and transmits artificial noise (AN). In order to reduce the non-cancellable self-interference due to the transmitted AN, the receiver has to estimate the self-interference channel prior to the data communication phase. In the proposed CT scheme, the receiver transmits a limited number of pilot symbols that are known only to itself. Such a secret CT scheme prevents an eavesdropper from estimating the jamming channel from the receiver to the eavesdropper, hence effectively degrading the eavesdropping capability. We analytically examine the connection probability (i.e., the probability of the data being successfully decoded by the receiver) of the legitimate channel and the secrecy outage probability due to eavesdropping for the proposed secret CT scheme. Based on our analysis, the optimal power allocation between CT and data/AN transmission at the legitimate transmitter/receiver is determined. Our examination shows that the newly proposed secret CT scheme significantly outperforms the non-secret CT scheme that uses publicly known pilots when the number of antennas at the eavesdropper is larger than one.
Owing to the openness of wireless channels, ensuring the security of communication for massive multiple-input multiple-output (MIMO) systems faces severe challenges. For the massive MIMO system in the presence of a full-duplex (FD) multi-antenna eavesdropper, a dual artificial-noise (AN) injection scheme is proposed to enhance communication security in this paper. Specifically, AN is superimposed onto the transmitted pilot signals to interfere with the eavesdropper from estimating the legitimate user channel in pilot training phases. In the phase of data transmission, the AN generated in the null space of the legitimate user is introduced to prevent the eavesdropper from receiving the confidential messages. Meanwhile, an iterative optimization algorithm is presented to obtain the optimal power allocation between the information-bearing signals and the AN for the potential countermeasures taken by the eavesdropper. Numerical results are presented to validate the superior performance of the proposed scheme in security ensurance compared to the conventional ones with AN injection schemes.
Achieving secure transmission in wireless network is a significantly important research topic. Classic cryptography encrypts a confidential message to an unreadable cipher message. Thus only the authentic receiver with correct secrecy key is able to decrypt the message. However, with the growing computational capability of adversaries, the requirement of secrecy key generation and distribution is getting stringent. Another method to achieve wireless security, which has attracted much attention in recent years, is through physical layer processing, named physical layer security. In a typical wiretap channel model consisting of a transmitter, a legal receiver and an adversary (illegal receiver), early works have proven that it is possible to achieve positive secrecy rate using multiple antenna techniques, such as beamforming, at the transmitter. In this thesis, we focus on two types of malicious behaviors of the adversary: passive eavesdropping and active attack. For the passive eavesdropping, we first consider the multi-input-single-output (MISO) wiretap channel, in which the legitimate transmitter utilizes the artificial noise aided precoding strategy to maximize the achievable secrecy rate of the channel. Both scenarios of known and unknown channel state information (CSI) for the eavesdropper channels are considered. By deriving the closed-form expression of ergodic secrecy rate, we prove that there exists an optimal power ratio between the information signal and the artificial noise. We then extend our study to a four-node fading channel model in a wireless relay network, which includes two single-antenna users, one single-antenna eavesdropper and one relay node equipped with multiple antennas. By studying the decode-and-forward (DF) scheme, cooperative jamming (CJ) scheme and one proposed hybrid relay scheme, relay-and-jamming (RJ), we aims to find the optimal relay scheme with the condition that the transmitter and the relay node are under individual power constraints and the CSI of the illegitimate channel is only statistically known. Our analysis shows that the hybrid RJ scheme is optimal when the transmitter has a relatively small power budget and/or the transmitter is far away from the intended receiver. Besides the passive eavesdropping, the adversary could also choose the active attack. The pilot spoofing attack is one active attack conducted by the adversary during the channel estimation phase of the legitimate transmission. In practical systems, the pilot signals are usually known \textit{a priori} and repeatedly used information. In this attack, an intelligent adversary spoofs the transmitter on the estimation of CSI by sending the identical pilot signal as the legitimate receiver. By doing so, the adversary could obtain a larger channel rate in the data transmission phase, and also drastically weaken the strength of the received signal at the legitimate receiver if the adversary utilizes large enough power. Due to the serious consequences caused by such an attack, we first propose an energy ratio detector (ERD) that explores the asymmetry of received signal power levels at the transmitter and the legitimate receiver when the attack occurs. Our analysis shows that the ERD could provide very high probability of detection with certain requirement on the false alarming probability. Furthermore, we design a two-way training based scheme to provide not only attack detection but also secure transmission. The two-way training based detector (TWTD) exploits the intrusive component created by the adversary, followed by a secure beamforming-assisted data transmission. In addition to the good detection performance, our scheme could estimate both legitimate and illegitimate channels, with which the beamforming could be designed for data transmission.
This paper proposes a novel secure channel estimation technique to provide security against leakage of the channel estimates to any malicious user by utilizing artificial noise (AN) along with full-duplex (FD) transmissions. AN overcomes the drawback of FD transmission, where any strategically located eavesdropper can minimize the interference signal received from the FD receiver. The proposed secure channel estimation technique comprises three stages, where the first stage is responsible for the estimation of the residual self-interference (SI) channel. The second stage acquires rough channel estimates to design AN orthogonal to the channel between legitimate transmitter-receiver for the next training stage. In the third stage, both legitimate nodes transmit orthogonal AN signals along with the known training signals using FD transmissions. For power allocation, we have presented a novel local adaptive power allocation algorithm at each legitimate node to allocate the powers to the training signals, and AN signals while ensuring equivocation at the eavesdropper. We provide the mean square error (MSE) to indicate the performance achieved by the respective nodes. We have also provided the bit error rate (BER) simulation analysis to indicate the secure communication achieved by securing the channel estimation process. The presented simulation analysis indicates that the eavesdropper is unable to decode the transmitted information while the legitimate receiver has robustly decoded the transmitted information.
Physical layer security is an important component of Wi-Fi communication systems, which are aimed at offering comfortable and personal record transmission among legitimate customers. In this context, full-duplex (FD) more than one-input more than one-output (MIMO) structures have won large interest due to their capability to transmit and receive facts simultaneously within the identical frequency band, thus increasing the spectral performance. However, the FD MIMO systems are at risk of eavesdropping attacks from unauthorized customers because of their high transmits power and self-interference. To cope with this trouble, the concept of secure FD MIMO wiretap channels has been added, which makes use of sign processing techniques, including beam forming and synthetic noise era, to cozy the transmission from eavesdroppers. The main project of these structures is to mitigate self-interference by concurrently maintaining an excessive signal-to-noise ratio (SNR) for the legitimate receiver and a low SNR for the eavesdropper. Several strategies, including strength manipulation, channel estimation, and topquality beam forming, were proposed to enhance the secrecy performance in FD MIMO structures. Those improvements in physical layer safety in FD MIMO wiretap channels have the potential to beautify the security of Wi-Fi communiqué structures and defend personal privacy.
In this paper, secure communication over a multi-input multi-output multi-eavesdropper (MIMÓME) wiretap channel is considered. We propose an enhanced MIMÓME artificial noise (AN) model in which the receiver (Bob) adopts the latest Full-Duplex MIMO Radio technique to emit AN jointly with the transmitter (Alice). An achievable secrecy rate is obtained for this model over an unfavorable noiseless eavesdropping channel. Optimization problem is formulated to solve the beamforming and power allocation for Alice and Bob's transmitting signals and to determine the dimension allocation between the information and AN signals. Simulations are carried out to illustrate the optimization process, and the results show that the enhanced MIMÓME model outperforms existing AN models for low self-interference regime.