In this paper, we investigate the physical-layer security of single-input single-output uplink single-carrier frequency-domain equalization (SC- FDE). A legitimate transmitter, Alice, sends confidential data messages to a legitimate receiver, Bob, in the presence of a passive eavesdropper, Eve. To secure her transmissions, Alice adds a time-domain artificial noise (AN) signal into each transmission block. The AN precoder is designed carefully to degrade Eve's receiver performance without affecting Bob's receiver performance. We investigate the impact of the transmit power allocation between data and AN signals on the average secrecy rate. Moreover, we consider three detection strategies at both Bob and Eve; namely, the zero-forcing (ZF) detector, linear minimum mean-square error (MMSE) detector and maximum likelihood (ML) detector. We investigate the correlation properties of the temporal AN symbols and illustrate if/how each detection strategy can exploit this correlation to reduce the AN effect on Eve. Furthermore, we highlight the tradeoffs between the complexities and average secrecy rates of the three detection strategies and we derive a closed-form expression for the average secrecy rate at high input SNR under the worse-case scenario when Eve performs ML detection.
In this paper, we investigate the physical-layer security of single-input single-output uplink single-carrier frequency-domain equalization (SC- FDE). A legitimate transmitter, Alice, sends confidential data messages to a legitimate receiver, Bob, in the presence of a passive eavesdropper, Eve. To secure her transmissions, Alice adds a time-domain artificial noise (AN) signal into each transmission block. The AN precoder is designed carefully to degrade Eve's receiver performance without affecting Bob's receiver performance. We investigate the impact of the transmit power allocation between data and AN signals on the average secrecy rate. Moreover, we consider three detection strategies at both Bob and Eve; namely, the zero-forcing (ZF) detector, linear minimum mean-square error (MMSE) detector and maximum likelihood (ML) detector. We investigate the correlation properties of the temporal AN symbols and illustrate if/how each detection strategy can exploit this correlation to reduce the AN effect on Eve. Furthermore, we highlight the tradeoffs between the complexities and average secrecy rates of the three detection strategies and we derive a closed-form expression for the average secrecy rate at high input SNR under the worse-case scenario when Eve performs ML detection.
We investigate the physical-layer security of uplink single-carrier frequency-division multiple-access (SC-FDMA) systems. Multiple users, Alices, send confidential messages to a common legitimate base-station, Bob, in the presence of an eavesdropper, Eve. To secure the legitimate transmissions, each user superimposes an artificial noise (AN) signal on the time-domain SC-FDMA data symbol. We reduce the computational and storage requirements at Bob's receiver by assuming simple per-sub-channel detectors. We assume that Eve has global channel knowledge of all links in addition to high computational capabilities, where she adopts high-complexity detectors such as single-user maximum likelihood (ML), multi-user minimum-mean-square-error, and multi-user ML. We analyze the correlation properties of the time-domain AN signal and illustrate how Eve can exploit them to reduce the AN effects. We prove that the number of useful AN streams that can degrade Eve's signal-to-noise ratio is dependent on the channel memories of Alices-Bob and Alices-Eve links. Furthermore, we enhance the system security for the case of partial Alices-Bob channel knowledge at Eve, where Eve only knows the precoding matrices of the data and AN signals instead of knowing the entire Alices-Bob channel matrices, and propose a hybrid security scheme that integrates temporal AN with channel-based secret key extraction.
A frequency domain (FD) time-reversal (TR) precoder is proposed to perform physical layer security (PLS) in single-input single-output (SISO) systems using orthogonal frequency-division multiplexing (OFDM) and artificial noise (AN) signal injection. The AN signal does not corrupt the data transmission to the legitimate receiver but degrades the decoding performance of the eavesdropper. This scheme guarantees the secrecy of a communication towards a legitimate user when the transmitter knows the instantaneous channel state information (CSI) of the legitimate link thanks to the channel reciprocity in time division duplex (TDD) systems, but does not know the instantaneous CSI of a potential eavesdropper. Three optimal decoding structures at the eavesdropper are considered in a fast fading (FF) environment depending on the handshake procedure between Alice and Bob. Closed-form approximations of the AN energy to inject in order to maximize the SR of the communication are derived. In addition, the required conditions at the legitimate receiver's end to guarantee a given SR are determined when Eve's signal-to-noise ratio (SNR) is infinite. Furthermore, a waterfilling power allocation strategy is presented to further enhance the secrecy of the scheme. Simulation results are presented to demonstrate the security performance of the proposed secure system.
We investigate the physical layer security of wireless single-input single-output orthogonal-division multiplexing (OFDM) when a transmitter, which we refer to as Alice, sends her information to a receiver, which we refer to as Bob, in the presence of an eavesdropping node, Eve. To prevent information leakage, Alice sends an artificial-noise (AN) signal superimposed over her information signal. We investigate the impact of the channel delay spread, OFDM cyclic prefix, information/AN power allocation, and information and AN precoders design on the achievable average secrecy rate. We consider the two cases of known and unknown channel state information (CSI) at Alice. Furthermore, we compare both cases of per-sub-channel processing and joint sub-channels processing at Eve's receiver. Our numerical results show the gains of AN injection in terms of average secrecy rate for different OFDM operating conditions. Moreover, based on our new insights, we demonstrate that the AN-aided scheme is effective and achieves almost the same average secrecy rate as the full-CSI case without the need for Eve's instantaneous CSI at Alice.
A frequency domain time-reversal (TR) precoder is proposed to perform physical layer security in single-input single-output (SISO) systems using orthogonal frequency-division multiplexing (OFDM) and artificial noise (AN) injection. This scheme guarantees the secrecy of a communication towards a legitimate user, Bob, by exploiting the frequency diversity selective behaviour in multipath channels. The transmitter, Alice, has imperfect channel state information (CSI) of the legitimate link thanks to the channel reciprocity in time division duplex systems and does not know the instantaneous CSI of a potential eavesdropper, Eve. Three optimal decoding structures at Eve are considered in a block fading environment depending on the handshake procedure between Alice and Bob. Closed-form approximations of the signal-to-noise ratio required at Bob and the maximal CSI error that can be made at Alice, in order to guarantee a communication ergodic secrecy rate (ESR), are derived. Furthermore, the optimal amount of AN energy to inject, considering imperfect CSI, is also given as a closed-form expression. A trade-off on the choice of the spreading factor of the TR precoder is established between maximizing the ESR and decreasing theϵ−achievable secrecy rate. Finally, thanks to these results, Alice can be a priori aware of the ESR over which she can establish a secure communication.
An increasing number of devices exchanges data via the wireless medium into large scale, decentralized, and heterogeneous networks, leading to the concept of Internet of Things (IoT). This PhD work proposes a new practical scheme to perform physical layer security (PLS) in this IoT context.Wireless communications in IoT networks are prone to passive eavesdropping. Therefore, this work introduces a scheme that guarantees the reliability of a communication from a transmitter (Alice) towards a legitimate user (Bob), while preventing multiple passive eavesdroppers (Eve) to correctly decode the data in a worst-cases scenario, thereby considering i) Eve to be noiseless, ii) Eve equipped with an arbitrarily large number of antennas, iii) Alice imperfectly estimating Bob's channel state information (CSI). To do so, a frequency domain time-reversal (TR) precoder is proposed using orthogonal frequency-division multiplexing (OFDM) and artificial noise (AN) injection. The scheme exploits the frequency diversity selective behaviour in multipath channels, and can be incorporated into existing standards, such as in LTE or 5G networks. Different configurations are investigated, namely, single-input single-output (SISO), multiple-input single-output (MISO), and single-input multiple-output (SIMO) systems.The handshake procedures between Alice and Bob are described, both in time-division duplexing (TDD) and frequency-division duplexing (FDD) systems, highlighting the amount of CSI acquisition at Eve, which influences the secrecy performances. Depending on the handshake procedures, different decoding structures are investigated at Eve for each system configuration, considering a block-fading environment. Closed-form approximations of the signal-to-noise ratio required at Bob and the maximal CSI error that can be made at Alice, in order to guarantee a communication ergodic secrecy rate (ESR), are derived. Furthermore, the optimal amount of AN energy to inject, as well as the maximal number of eavesdropper's antennas allowed, considering imperfect CSI, are also given as closed-form expressions. A trade-off on the choice of the spreading factor of the TR precoder is established between maximizing the ESR and decreasing the percentage of outage, leading to information leaked to Eve. Finally, thanks to these results, Alice can be a-priori aware of the ESR over which she can establish a secure communication, assuming worst-case assumptions regarding the eavesdroppers. The PLS scheme presented in this PhD work therefore emerges as a promising solution to secure wireless communications in IoT networks.
This paper investigates artificial noise (AN) injection along the temporal and spatial dimensions of a legitimate system to secure its transmissions from potential eavesdropping. In particular, we consider a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system in the presence of a multiple-antenna passive eavesdropper and characterize both the secrecy rate and average secrecy rate of the legitimate system. We assume that the legitimate transmitter knows the full channel state information (CSI) of the links connecting it with its legitimate receiver but does not know the instantaneous CSI of the passive eavesdropper. Closed-form expressions for the secrecy rate and average secrecy rate are derived for the asymptotic case of a large number of transmit antennas. We compare the degrading effects of spatial and temporal AN on the eavesdropper's rate. We also investigate the power allocation between the data and the AN and the power allocation between the spatial and the temporal AN. An upper bound on the secrecy rate loss due to the presence of the eavesdropper is also derived, and computer simulations are carried out to demonstrate the performance of our proposed AN scheme.