In this paper, we exploit the potential benefits of machine learning in enhancing physical layer security in cooperative wireless networks. We focus on the case where multiple relays adopt amplify-and-forward (AF) relaying to forward information from the source to the destination. It is assumed that the global channel state information (CSI) of the legitimate links and wiretap links is available to the source. The optimal relay is selected to improve physical layer security against eavesdropping. By modeling the problem of the relay selection as a multi-class classification problem, a neural network (NN) based scheme is proposed to select the optimal relay which guarantees the perfect secrecy performance of the relay cooperative communication system. Compared with the conventional relay selection scheme, the simulation results show that our proposed scheme not only achieves almost the same secrecy performance, but also has advantage of relatively small feedback overhead. The work presented here provides insights into the new design of relay selection based on machine learning.
In this paper, we exploit the potential benefits of machine learning in enhancing physical layer security in cooperative wireless networks. We focus on the case where multiple relays adopt amplify-and-forward (AF) relaying to forward information from the source to the destination. It is assumed that the global channel state information (CSI) of the legitimate links and wiretap links is available to the source. The optimal relay is selected to improve physical layer security against eavesdropping. By modeling the problem of the relay selection as a multi-class classification problem, a neural network (NN) based scheme is proposed to select the optimal relay which guarantees the perfect secrecy performance of the relay cooperative communication system. Compared with the conventional relay selection scheme, the simulation results show that our proposed scheme not only achieves almost the same secrecy performance, but also has advantage of relatively small feedback overhead. The work presented here provides insights into the new design of relay selection based on machine learning.
Cooperative communication in wireless relay systems can improve the physical layer security, and the relay selection has great impacts on the security performances. In this paper the relay selection in Amplify-and-Forward (AF) cooperative networks is investigated. The system model constitutes of a source, an eavesdropper, a destination, and a number of intermediate nodes with secrecy constraints. The proposed optimal selection (OS) algorithm is based on the instantaneous channel state information (CSI) of two hops, jointly protects the target destination against eavesdropping and interference. To simplify the complexity of OS, the suboptimal selection (SS) algorithm is also presented, which is based on the instantaneous of the first hop and the statistical CSI of the second hop respectively. The secrecy capacity and secrecy outage probability of these two relay selection algorithms are analyzed. Simulation results of OS and SS validate our theoretical analysis and show enhancement in the secrecy rate over the direct transmission.
Privacy and security have an increasingly important role in wireless networks. A secure communication enables a legitimate destination to successfully retrieve information sent by a source, while it disables the eavesdropper (illegitimate destination) to interpret the intercepted information. Physical (PHY) layer security approaches for wireless communications can prevent eavesdropping without encryption. It exploits the physical characteristics of the wireless channel in order to transmit messages securely. They are typically feasible when the source-destination channel is better than the source-eavesdropper channel. Cooperative schemes are a means to improve the performance of secure wireless communications. We propose an improved relay selection scheme, based on source-eavesdropper channel SNR restriction, that will guarantee the best secrecy rate at the destination under QoS condition. Performance has been studied in terms of secrecy rate, outage probability and average error probability. Simulations shows that the proposed scheme outperforms in terms of the secrecy rate at the destination when compared to techniques in the literature.
Physical (PHY) layer security approaches for wireless communications can prevent eavesdropping without upper layer data encryption. However, they are hampered by wireless channel conditions: absent feedback, they are typically feasible only when the source-destination channel is better than the source-eavesdropper channel. Node cooperation is a means to overcome this challenge and improve the performance of secure wireless communications. This paper addresses secure communications of one source-destination pair with the help of multiple cooperating relays in the presence of one or more eavesdroppers. Three cooperative schemes are considered: decode-and-forward (DF), amplify-and-forward (AF), and cooperative jamming (CJ). For these schemes, the relays transmit a weighted version of a reencoded noise-free message signal (for DF), a received noisy source signal (for AF), or a common jamming signal (for CJ). Novel system designs are proposed, consisting of the determination of relay weights and the allocation of transmit power, that maximize the achievable secrecy rate subject to a transmit power constraint, or, minimize the transmit power subject to a secrecy rate constraint. For DF in the presence of one eavesdropper, closed-form optimal solutions are derived for the relay weights. For other problems, since the optimal relay weights are difficult to obtain, several criteria are considered leading to suboptimal but simple solutions, i.e., the complete nulling of the message signals at all eavesdroppers (for DF and AF), or the complete nulling of jamming signal at the destination (for CJ). Based on the designed relay weights, for DF in the presence of multiple eavesdroppers, and for CJ in the presence of one eavesdropper, the optimal power allocation is obtained in closed-form; in all other cases the optimal power allocation is obtained via iterative algorithms. Numerical evaluation of the obtained secrecy rate and transmit power results show that the proposed design can significantly improve the performance of secure wireless communications.
In this letter, we exploit the potential benefits of machine learning in enhancing physical layer security in multi-input multi-output multi-antenna-eavesdropper wiretap channels. To this end, we focus on the scenario where the source adopts transmit antenna selection (TAS) as the transmission strategy. We assume that the channel state information (CSI) of the legitimate receiver is available to the source, while the CSI of the eavesdropper can be either known or not known at the source. By modeling the problem of TAS as a multiclass classification problem, we propose two machine learning-based schemes, namely, the support vector machine-based scheme and the naive-Bayes-based scheme, to select the optimal antenna that maximizes the secrecy performance of the considered system. Compared to the conventional TAS scheme, we show that our proposed schemes can achieve almost the same secrecy performance with relatively small feedback overhead. The work presented here provides insights into the design of new machine learning-based secure transmission schemes.
In the last decade, multi-hop cooperation has evolved bringing several advantages including coverage improvement, more reliability of wireless links, and power consumption reduction. Still, its application has raised several challenges, such as the need for secure transmission at each hop, algorithms to perform relay selection and the accurate models to facilitate performance analysis. This paper addresses the problem of physical layer (PHY) security in a multi-hop wireless cooperative network, where communication at each hop is assisted by multiple relays forming a cluster, each cluster being surrounded by multiple eavesdroppers which together may tap transmissions from both the source and the relays. The main focus of the study is on analyzing the benefits of various relay selection schemes for protecting the source-destination transmission against the eavesdroppers, which can collude and combine information via diversity combining techniques. To be specific, four relay selection schemes, which differ in the way they employ available measures link quality, are considered to deliver the source information to the destination via a decode-and-forward (DF) strategy. To evaluate the security performance of the multi-hop cooperative link in the presence of colluding eavesdroppers, we derive novel closed-form analytical expressions for the secrecy outage probability (SOP) with consideration of special cases of practical interest.
In the last decade, multi-hop cooperation has evolved bringing several advantages including coverage improvement, more reliability of wireless links, and power consumption reduction. Still, its application has raised several challenges, such as the need for secure transmission at each hop, algorithms to perform relay selection and the accurate models to facilitate performance analysis. This paper addresses the problem of physical layer (PHY) security in a multi-hop wireless cooperative network, where communication at each hop is assisted by multiple relays forming a cluster, each cluster being surrounded by multiple eavesdroppers which together may tap transmissions from both the source and the relays. The main focus of the study is on analyzing the benefits of various relay selection schemes for protecting the source-destination transmission against the eavesdroppers, which can collude and combine information via diversity combining techniques. To be specific, four relay selection schemes, which differ in the way they employ available measures link quality, are considered to deliver the source information to the destination via a decode-and-forward (DF) strategy. To evaluate the security performance of the multi-hop cooperative link in the presence of colluding eavesdroppers, we derive novel closed-form analytical expressions for the secrecy outage probability (SOP) with consideration of special cases of practical interest.