Channel State Information Of Eavesdropper Research Articles

Improving Physical Layer Security for Reconfigurable Intelligent Surface Aided NOMA 6G Networks

The intrinsic integration of the nonorthogonal multiple access (NOMA) and reconfigurable intelligent surface (RIS) techniques is envisioned to be a promising approach to significantly improve both the spectrum efficiency and energy efficiency for future wireless communication networks. In this paper, the physical layer security (PLS) for a RIS-aided NOMA 6G networks is investigated, in which a RIS is deployed to assist the two "dead zone" NOMA users and both internal and external eavesdropping are considered. For the scenario with only internal eavesdropping, we consider the worst case that the near-end user is untrusted and may try to intercept the information of far-end user. A joint beamforming and power allocation sub-optimal scheme is proposed to improve the system PLS. Then we extend our work to a scenario with both internal and external eavesdropping. Two sub-scenarios are considered in this scenario: one is the sub-scenario without channel state information (CSI) of eavesdroppers, and another is the sub-scenario where the eavesdroppers' CSI are available. For the both sub-scenarios, a noise beamforming scheme is introduced to be against the external eavesdroppers. An optimal power allocation scheme is proposed to further improve the system physical security for the second sub-scenario. Simulation results show the superior performance of the proposed schemes. Moreover, it has also been shown that increasing the number of reflecting elements can bring more gain in secrecy performance than that of the transmit antennas.

Physical Layer Security Assisted Computation Offloading in Intelligently Connected Vehicle Networks

In this paper, we propose a secure computationoffloading scheme (SCOS) in intelligently connected vehicle (ICV) networks, aiming to minimize overall latency of computing via offloading part of computational tasks to nearby servers in small cell base stations (SBSs), while securing the information delivered during offloading and feedback phases via physical layer security. Existing computation offloading schemes usually neglected time-varying characteristics of channels and their corresponding secrecy rates, resulting in an inappropriate task partition ratio and a large secrecy outage probability. To address these issues, we utilize an ergodic secrecy rate to determine how many tasks are offloaded to the edge, where ergodic secrecy rate represents the average secrecy rate over all realizations in a time-varying wireless channel. Adaptive wiretap code rates are proposed with a secrecy outage constraint to match time-varying wireless channels. In addition, the proposed secure beamforming and artificial noise (AN) schemes can improve the ergodic secrecy rates of uplink and downlink channels even without eavesdropper channel state information (CSI). Numerical results demonstrate that the proposed schemes have a shorter system delay than the strategies neglecting time-varying characteristics.

Artificial Noise-Aided Secure Relay Communication With Unknown Channel Knowledge of Eavesdropper

In this article, a new relay-aided secure communication system is investigated, where a transmitter sends signals to a destination via an amplify-and-forward (AF) relay in the presence of an eavesdropper. We consider a general system configuration, where the source, relay, destination, and eavesdropper are all equipped with multiple antennas. In the practical scenarios of unknown eavesdropper's channel state information (CSI) and uncertainty of the eavesdropper's location, we aim to maximize the expected value of the system secrecy rate over the presumed distribution of the eavesdropper's channels, by exploiting the artificial noise (AN) transmitted by the source and relay nodes. The system design issue is formulated as a nonconvex stochastic optimization problem with a source transmission power constraint and a nonconvex relay transmission power constraint. A novel computational method is proposed to solve this challenging problem. The new method is developed based on an exact penalty function method together with a parallel stochastic decomposition algorithm. Numerical simulations are performed to study the effectiveness of the proposed scheme at various locations of the eavesdropper. Simulation results show that for most cases, secure communication can be achieved without the CSI knowledge of eavesdropper's channels, and the achievable secrecy rate follows the trend of a benchmark system where the eavesdropper's full CSI is available. In particular, the achievable system secrecy rate increases with the number of antennas at the legitimate users. Moreover, the optimal power allocated for the transmission of the AN increases with the system signal-to-noise ratio. The proposed computational method achieves a higher system secrecy rate than a conventional penalty function based approach.

A Product Channel Attack to Wireless Physical Layer Security

We propose a novel attack that compromises the physical layer security in wireless systems with eavesdropper's channel state information at the transmitter side. This technique is based on the transmission of a slowly-varying random symbol by the eavesdropper during its uplink transmission, so that the equivalent fading channel observed at the base station (BS) has a larger variance. Then, the BS designs the secure downlink transmission under the assumption that the eavesdropper's channel experiences a larger fading severity than in reality. We show that this approach can lead the BS to transmit to Bob at a rate larger than the secrecy capacity, thus compromising the system secure operation. Our analytical results, corroborated by simulations, show that the use of multiple antennas at the BS may partially alleviate but not immunize against these type of attacks.

Secure Communication With Energy-Harvesting Buffer-Aided Jammer

Information security and self-sustainability are crucial to resource-limited wireless networks. In this paper, we assess the secrecy performance of the legitimate link without having eavesdropper's channel state information (CSI) while considering an energy harvesting (EH) jammer with finite and infinite energy buffer sizes. The EH jammer utilizes accumulated energy from its buffer and transmits artificial noise (AN) to ensure secure communication. To manage the uncertainty in harvested energy and consumption, we analyze on-off (OO) jamming and always-on (AO) jamming schemes. The analytical expressions are obtained for secrecy outage probability (SOP). This analysis models the energy arrival and departure process by a discrete-time continuous-state Markov chain to eliminate the computational complexity and inaccuracy of a discrete-state Markov chain. Both the schemes are compared using SOP and secure throughput. This analysis shows the adequacy of a finite buffer for an EH jammer and also the fact that the availability of jamming power has a more pronounced effect on SOP as compared to a larger number of antennas at the jammer.

Optimization of pre-processing filter for time-reversal multi-user secure transmission systems based on artificial noise

Physical layer security is a way to realize the secure transmission of information by employing the characteristics of wireless channels. Thanks to its spatial and temporal focusing property, the time-reversal (TR) transmission can achieve effective secure communications even when the transmitter is only equipped with one antenna. This paper studies the design and optimization of the security scheme based on artificial noise (AN) with or without the eavesdropper's channel state information (ECSI) in a TR multi-user downlink multiple access system. The null-space AN is adopted when ECSI is unavailable, and the corresponding optimization problem is to minimize the signal power under each user's signal-to-interference-plus-noise ratio (SINR) target constraint, so that the power used to send AN is maximized and the interception rate of the eavesdropper is minimized. The problem is solved by transforming it into a semidefinite program (SDP) with semidefinite relaxation (SDR). The pre-processing filter and AN are jointly optimized to maximize the sum secrecy rate when ECSI is available. The problem is solved by transforming it into a convex program by using SDR and the first-order Taylor approximation. Simulation results show that the sum secrecy rate of the proposed scheme is significantly higher than that of the conventional TR transmission system with or without AN.

Power Allocation and Outage Analysis for Secure MISO Cognitive Radio Networks With an Unknown Eavesdropper

This paper investigates the power allocation problem for secure secondary transmission in a multiple-input single-output cognitive wiretap system with artificial noise (AN). The secondary transmitter exchanges confidential information with the secondary destination in the presence of an unknown eavesdropper. Since the eavesdropper's channel state information (CSI) is unavailable, we propose an optimal adaptive power allocation scheme, and derive a closed-form expression of the optimal power allocation factor that minimizes the secrecy outage probability (SOP). A suboptimal fixed power allocation scheme is also proposed to reduce the system complexity. Moreover, exact closed-form expressions of SOP under both schemes are derived. Numerical results are provided to corroborate the accuracy of our analytical results and the superiority of the proposed schemes to the benchmarks.

Power Efficient Secure Full-Duplex SWIPT Using NOMA and D2D with Imperfect CSI.

The secure full-duplex (FD) simultaneous wireless information and power transfer (SWIPT) system and non-orthogonal multiple access (NOMA) have been deemed two promising technologies for the next generation of wireless communication. In this paper, the network is combined with device-to-device (D2D) and a practical bounded channel state information (CSI) estimation scheme. A system total transmit power minimization problem is studied and formulated as a multi-objective optimization (MOO) problem via the weighted Tchebycheff approach. A set of linear matrix inequalities (LMI) is used to transform the non-convex form of constraints into the convex form. Considering the imperfect CSI of the potential eavesdropper for robust power allocation, a bounded transmission beamforming vector design along with artificial noise (AN) is used, while satisfying the requirements from the secrecy rates as well as the energy harvesting (EH) task. Numerical simulation results validate the convergence performance and the trade-off between the uplink (UL) and downlink (DL) data transmit power. It is also shown that by FD and NOMA, the performance of the proposed algorithm is higher than that of half-duplex (HD) and orthogonal multiple access (OMA).

Cooperative Jamming for Secure Transmission With Both Active and Passive Eavesdroppers

Secrecy transmission is investigated for a cooperative jamming scheme, where a multi-antenna jammer generates artificial noise (AN) to confuse eavesdroppers. Two kinds of eavesdroppers are considered: passive eavesdroppers who only overhear the legitimate information, and active eavesdroppers who not only overhear the legitimate information but also jam the legitimate signal. Existing works only treat the passive and active eavesdroppers separately. Different from the existing works, we investigate the achievable secrecy rate in presence of both active and passive eavesdroppers. For the considered system model, we assume that the instantaneous channel state information (CSI) of the active eavesdroppers is available at the jammer, while only partial CSI of the passive eavesdroppers is available at the jammer. A new zero-forcing beamforming scheme is proposed in the presence of both active and passive eavesdroppers. For both the perfect and imperfect CSI cases, the total transmission power allocation between the information and AN signals is optimized to maximize the achievable secrecy rate. Numerical results show that imperfect CSI between the jammer and the legitimate receiver will do more harm to the achievable secrecy rate than imperfect CSI between the jammer and the active eavesdropper.

Enhancing Secure MIMO Transmission via Intelligent Reflecting Surface

In this article, we consider an intelligent reflecting surface (IRS) assisted Guassian multiple-input multiple-output (MIMO) wiretap channel (WTC), and focus on enhancing its secrecy rate. Due to MIMO setting, all the existing solutions for enhancing the secrecy rate over multiple-input single-output WTC completely fall to this work. Furthermore, all the existing studies are simply based on an ideal assumption that full channel state information (CSI) of eavesdropper (Ev) is available. Therefore, we propose numerical solutions to enhance the secrecy rate of this channel under both full and no Ev's CSI cases. For the full CSI case, we propose a barrier method and one-by-one (OBO) optimization combined alternating optimization (AO) algorithm to jointly optimize the transmit covariance R at transmitter (Tx) and phase shift coefficient Q at IRS. For the case of no Ev's CSI, we develop an artificial noise (AN) aided joint transmission scheme to enhance the secrecy rate. In this scheme, a bisection search (BS) and OBO optimization combined AO algorithm is proposed to jointly optimize R and Q. Such scheme is also applied to enhance the secrecy rate under a special scenario in which the direct link between Tx and receiver (Rx)/Ev is blocked due to obstacles. In particular, we propose a BS and minorization-maximization (MM) combined AO algorithm with slightly faster convergence to optimize R and Q for this scenario. Simulation results have validated the monotonic convergence of the proposed algorithms, and it is shown that the proposed algorithms for the IRS-assisted design achieve significantly larger secrecy rate than the other benchmark schemes under full CSI. When Ev's CSI is unknown, the secrecy performance of this channel also can be enhanced by the proposed AN aided scheme, and there is a trade-off between increasing the quality of service at Rx and enhancing the secrecy rate.

Resource Allocation for Enhancing Offloading Security in NOMA-Enabled MEC Networks

This paper studies an uplink nonorthogonal multiple access (NOMA)-enabled mobile-edge computing network. Specifically, we focus on the practical design of secure offloading without knowing the eavesdropper's channel state information. The aim is to maximize the minimum antieavesdropping ability (AEA) for uplink NOMA users subject to the worst-case secrecy rate requirements and limited transmission power budgets. The formulated problem is nonconvex and difficult to be solved directly. In order to tackle this issue, we propose an efficient iterative algorithm by jointly designing the secrecy rate, local computing bits, and power allocation. The local computing bits and the power allocation are derived in closed form. Numerical results are provided to demonstrate the efficiency of our proposed scheme in terms of AEA.

Power Optimization for Enhancing Secrecy of Cooperative User Relaying NOMA Networks

To enhance the secrecy of wireless transmission, we propose a cooperative user relaying NOMA scheme, in which the near user works in full-duplex mode by transmitting jamming signals and receiving desired signals in the first phase, and the base station sends jamming signals in the second phase. Two power allocation (PA) schemes between the legitimate and jamming signals are designed based on different knowledge of the eavesdropping channel state information (ECSI). The first scheme aims to jam the eavesdropping with highest power while meeting rate requirements without ECSI. In the second scheme, the closed-form expressions of secrecy outage probability (SOP) are first derived using the statistical ECSI. Then, the sum secrecy rate is maximized by optimizing the PA and redundant rate with SOP constraints. Simulation results are provided to show the effectiveness of the proposed schemes.

Securing Multi-User Broadcast Wiretap Channels With Finite CSI Feedback

In this work, we investigate the problem of secure broadcasting over block-fading wiretap channels with limited channel knowledge at the transmitter. More particularly, we analyze the effect of having a finite rate feedback on the throughput of multi-user broadcast wiretap channels. We consider that the transmitter is only provided by a $b$-bits feedback of the main channel state information (CSI) sent by each legitimate receiver, at the beginning of each fading block, over error-free public links with limited capacity. Also, we assume that the transmitter is aware of the statistics of the eavesdropper's CSI but not of its channel's realizations. Under these assumptions of CSI uncertainty, we characterize the ergodic secrecy capacity of the system when a common message is broadcasted to all legitimate receivers, the ergodic secrecy sum-capacity when multiple independent messages are transmitted, and the ergodic secrecy capacity region for the broadcast channel with confidential messages (BCCM). In all three scenarios, we show that as long as the transmitter has some knowledge of the main CSI, obtained even through a 1-bit CSI feedback, a non-zero secrecy rate can still be achieved. The impact of having the feedback sent over a binary erasure channel (BEC) is also investigated for the BCCM case. Here again, and even with the possibility of having the feedback bits erased, a positive secrecy rate can still be achieved as long as the erasure event is not a probability-one event. An asymptotic analysis of the obtained results is provided for the high SNR regime, and the scaling law of the system, when the number of legitimate receivers is large, is also presented.

Cooperative secure transmission against collusive eavesdroppers in Internet of Things

As Internet of Things (IoT) has boomed in recent years, many security issues have also been exposed. Focusing on physical layer security in wireless Internet of Things network communication, a series of security methods have been widely studied. Nevertheless, cooperative jamming methods in physical layer security to fight against collusive eavesdroppers have not been thoroughly studied yet. In this article, we study a cooperative-jamming-based physical layer secure transmission scheme for Internet of Things wireless networks in the presence of collusive eavesdroppers. We design a cooperative jamming strategy without knowing the channel state information of eavesdroppers. Considering the cooperation of multiple nodes with multiple antennas, this strategy can maximize the signal-to-interference-plus-noise ratio at an actuator (legitimate receiver). Meanwhile, the generated cooperative jamming signals can reduce the signal-to-interference-plus-noise ratio at eavesdroppers. To explore the theoretical security performance of our strategy, we perform a secrecy outage probability analysis and an asymptotic analysis. In the cases of cooperative jamming and without cooperative jamming, the closed-form expressions of the secrecy outage probability are deduced, and the influence of system parameters on the secrecy outage probability becomes more intuitive through a strict mathematical asymptotic behavior analysis. In addition, considering the energy limitation of Internet of Things devices, we propose a power allocation algorithm to minimize the total transmission power given the security requirements. The numerical results show the effectiveness of our schemes and are consistent with the theoretical analysis.

AN‐aided probabilistic robust and secure beamforming with imperfect LCSI and statistical ECSI

The probabilistic robust beamforming with the help of artificial noise (AN) is investigated in this study, where a multiple-input-single-output wiretap scenario with K single-antenna eavesdroppers is considered. Based on a more practical assumption that the transmitter derives imperfect legitimate user's channel state information (LCSI) and statistical eavesdroppers' channel state information (ECSI), secrecy rate maximisation (SRM) under a total transmit power constraint and K probabilistic secrecy outage constraints are studied. To deal with it, the K probabilistic constraints are firstly approximated to the deterministic worst-case ones by resorting to sphere bounding. Secondly, by introducing a slack variable the approximated worst-case SRM can be further recast as a series of semi-definite programmings. In this way, the jointly optimised robust beamforming vector and the AN covariance are determined in a tractable convex fashion. Moreover, the authors can prove that the derived AN-aided secure robust beamforming actually is the optimal solution to the approximated worst-case SRM problem. Numerical results reveal that the proposed AN-aided probabilistic secure robust beamforming could achieve outage secrecy rate improvement in comparison with the existing optimal worst-case robust beamforming without AN, optimal outage constrained robust beamforming without AN, the non-robust isotropic AN transmission, and the non-robust AN-aided beamforming scheme.

Joint relay and jammer selection for secure cooperative networks with a full‐duplex active eavesdropper

In this study, the authors investigate the secure transmission of a cooperative network, in which a source communicates with a destination via multiple cooperative nodes in the presence of a full-duplex active eavesdropper, which can intercept the confidential signals and transmit jamming signals simultaneously. To safeguard the security of legitimate communication, two joint relay and jammer selection schemes are proposed according to the availability of the eavesdropper's channel state information, namely, optimal relay and random jammer selection scheme and optimal relay and optimal jammer selection scheme. The authors first derive the exact closed-form expressions of the secrecy outage probability (SOP) for different selection schemes. Aiming at minimising SOP, they then adopt the deep feedforward neural network to determine the optimal power allocation between the selected relay and jammer. Further, the asymptotic expressions for SOP in the high signal-to-noise ratio regime are derived. Numerical results verify the analysis and demonstrate the performance advantage of the proposed scheme over conventional relay selection scheme with optimal power allocation.

Rethinking Secure Precoding via Interference Exploitation: A Smart Eavesdropper Perspective

Based on the concept of constructive interference (CI), multiuser interference (MUI) has recently been shown to be beneficial for communication secrecy. A few CI-based secure precoding algorithms have been proposed that use both the channel state information (CSI) and knowledge of the instantaneous transmit symbols. In this article, we examine the CI-based secure precoding problem with a focus on smart eavesdroppers that exploit statistical information gleaned from the precoded data for symbol detection. Moreover, the impact of correlation between the main and eavesdropper channels is taken into account. We first modify an existing CI-based precoding scheme to better utilize the destructive impact of the interference. Then, we point out the drawback of both the existing and the new modified CI-based precoders when faced with a smart eavesdropper. To address this deficiency, we provide a general principle for precoder design and then give two specific design examples. Finally, the scenario where the eavesdropper's CSI is unavailable is studied. Numerical results show that although our modified CI-based precoder can achieve a better energy-secrecy trade-off than the existing approach, both have a limited secrecy benefit. On the contrary, the precoders developed using the new CI-design principle can achieve a much improved tradeoff and significantly degrade the eavesdropper's performance.

Physical Layer Security for Wireless Powered Massive MIMO Decode and Forward Relay Systems with Hardware Impairments: Performance Analysis

In this paper, the issue of secrecy capacity of wireless powered massive MIMO dual hop relay system with a single antenna eavesdropper having non ideal hardware is addressed. The relay harvests energy in a proportionate manner and passes it to destination through beamforming with classical decode and forward relaying protocol. The relay has no channel state information (CSI) of passive eavesdropper but has CSI of the legitimate channel. The work presented in this paper focuses on the analysis of the difference in system performance with ideal and non ideal hardware, bounded by strict outage probability. The performance (in terms of secrecy outage capacity) is studied with hardware impairments (HWIs) defined for all network elements, i.e., source, relay, destination and passive eavesdropper. It is also observed that compared to ideal hardware, there is significant degradation in performance due to HWIs.

An Anti-Eavesdropping Strategy for Precoding-Aided Spatial Modulation With Rough CSI of Eve

In this paper, an anti-eavesdropping strategy is proposed for secure precoding-aided spatial modulation networks, under the assumption that the rough channel state information of eavesdropper can be obtained at the transmitter. Traditionally, artificial noise (AN) can be always projected into the null-space of the legitimate channel, however it may lead to some security loss since this strategy dispenses with a holistic consideration for secure transmissions. To reduce the computational complexity of our optimization problem, we derive a closed-form expression that is a loose bound of the approximate rate over the illegitimate channel. Then a concave maximization problem is formulated for optimizing the covariance matrix of AN. Simulation results show that our proposed low-complexity scheme performs closely to the method which directly maximizes the approximate secrecy rate expression, and harvests significant secrecy rate gains compared with the traditional null-space projection benchmark.

Data-Driven Relay Selection for Physical-Layer Security: A Decision Tree Approach

Conventional optimization-driven secure relay selection relies on maximization algorithm and accurate channel state information (CSI) of both legitimate and eavesdropper channels. Particularly, estimating and collecting accurate eavesdropper CSI is a difficult task. In this paper, we exploit the benefits of machine learning in solving secure relay selection problem from a data-driven perspective. We convert secure relay selection to a multiclass-classification problem and solve it by a decision-tree-based scheme, which is composed of three phases - preparing training data, building decision tree and predicting relay selection. To meet decision tree’s requirement that input features must take discrete values, a feature extraction method is proposed to generate discrete input by quantizing the accurate CSI of legitimate and eavesdropper channels. By this means, the decision-tree-based relay selection only requires quantized CSI feedback which takes substantially fewer bits in predicting phase. For the purpose of optimizing quantization parameters and enhancing decision tree prediction, we further derive three splitting criteria, i.e. information gain, information gain ratio and Gini index. Simulation results show that if the quantization parameters are set properly, the proposed decision-tree-based scheme can achieve satisfactory performance in terms of average secrecy rate while reducing computational complexity and feedback amount.