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Entropy

Intelligent Reflecting Surface–Assisted Wireless Secret Key Generation against Multiple Eavesdroppers

Ya Liu, Kaizhi Huang, Xiaoli Sun, Shaochuan Yang, Liang Wang

Published Mar 23, 2022• 3 citations
Publisher

Abstract

In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user's SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex-concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.

DOI
10.3390/e24040446

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In this paper, we propose an improved physical layer key generation scheme that can maximize the secret key capacity by deploying intelligent reflecting surface (IRS) near the legitimate user aiming at improving its signal-to-noise ratio (SNR). We consider the scenario of multiple input single output (MISO) against multiple relevant eavesdroppers. We elaborately design and optimize the reflection coefficient matrix of IRS elements that can improve the legitimate user's SNR through IRS passive beamforming and deteriorate the channel quality of eavesdroppers at the same time. We first derive the lower bound expression of the achievable key capacity, then solve the optimization problem based on semi-definite relaxation (SDR) and the convex-concave procedure (CCP) to maximize the secret key capacity. Simulation results show that our proposed scheme can significantly improve the secret key capacity and reduce hardware costs compared with other benchmark schemes.
Physical-layer key generation (PKG) can generate symmetric keys between two communication ends based on the reciprocal uplink and downlink channels. By smartly reconfiguring the radio signal propagation, intelligent reflecting surface (IRS) is able to improve the secret key rate of PKG. However, existing works involving IRS-assisted PKG are concentrated in single-antenna wireless networks. So this paper investigates the problem of PKG in the IRS-assisted multiple-input single-output (MISO) system, which aims to maximize the secret key rate by optimally designing the IRS passive beamforming. First, we analyze the correlation between channel state information (CSI) of eavesdropper and legitimate ends and derive the expression of the upper bound of secret key rate under passive eavesdropping attack. Then, an optimal algorithm for designing IRS reflecting coefficients based on Semi-Definite Relaxation (SDR) and Taylor expansion is proposed to maximize the secret key rate. Numerical results show that our optimal IRS-assisted PKG scheme can achieve much higher secret key rate when compared with two benchmark schemes.
Physical layer secret key generation (SKG) is a promising supplement for high-level encryption, which leverages the channel reciprocity and the natural randomness of wireless channel. However, practical implementations often exhibit static environment. To solve this problem, this paper proposes a novel secret key generation scheme assisted by an intelligent reflecting surface (IRS) which can smartly reconfigure the radio signal propagation to improve the secret key rate of SKG. Specially, we formulate the minimum achievable secret key capacity in the IRS-assisted multiple-input single-output (MISO) system with multiple eavesdroppers. Then, an optimization framework for designing IRS reflecting coefficients based on the secret key capacity lower bound is proposed. Numerical results show that our optimal IRS-assisted SKG scheme can achieve much higher achievable secret key capacity when compared with two benchmark schemes.
We propose and analyze secret key generation using intelligent reflecting surface (IRS) assisted wireless communication networks. To this end, we first formulate the minimum achievable secret key capacity for an IRS acting as a passive beamformer in the presence of multiple eavesdroppers. Next, we develop an optimization framework for the IRS reflecting coefficients based on the secret key capacity lower bound. To derive a tractable and efficient solution, we design and analyze a semidefinite relaxation (SDR) and successive convex approximation (SCA) based algorithm for the proposed optimization. Simulation results show that employing our IRS-based algorithm can significantly improve the secret key generation capacity for a wide-range of wireless channel parameters.
We propose and analyze secret key generation using intelligent reflecting surface (IRS) assisted wireless communication networks. To this end, we first formulate the minimum achievable secret key capacity for an IRS acting as a passive beamformer in the presence of multiple eavesdroppers. Next, we develop an optimization framework for the IRS reflecting coefficients based on the secret key capacity lower bound. To derive a tractable and efficient solution, we design and analyze a semidefinite relaxation (SDR) and successive convex approximation (SCA) based algorithm for the proposed optimization. Simulation results show that employing our IRS-based algorithm can significantly improve the secret key generation capacity for a wide-range of wireless channel parameters.
In secret key generation of physical layer security technology, it is challenging to achieve high key capacity and low bit inconsistency rate. This paper investigates intelligent reflecting surface (IRS)-assisted secret key generation, which aims to maximize the secret key capacity by adjusting the placement of the IRS units. Specifically, we first analyze and deduce the key capacity expression of the IRS-assisted system from the perspective of information theory. Then we investigate how to use the channel state information (CSI) to place the IRS units effectively so as to maximize the secret key capacity. Simulation results show that our scheme could improve the quality of secret key generation significantly.
Abstract Reconfigurable intelligent surface (RIS)‐assisted physical layer key generation plays an important role in the eavesdropping problem on a typical multi‐user scenario of wireless networks. Existing RIS‐assisted physical key generation technology mainly solved the security issues in the single‐antenna and multi‐user scenario, which is based on the idealistic assumption of a spatially independent channel model at the RIS. It limits the degrees of freedom and neglects the existence of channel spatial correlation, which would possibly degrade the sum key generation rate (SKGR). To solve the above problem, this paper proposes a secret key generation scheme for RIS‐assisted multiple‐input single‐output multi‐user system. This scheme establishes a spatial correlation channel model, which comprehensively considers the influence of spatial correlation among antennas of the base station (BS), multi‐user, and RIS elements on SKGR. Based on this, a key generation framework is designed to generate a more secure secret key with the maximum SKGR. Specifically, a closed‐form SKGR expression and an optimization problem formulation are obtained to obtain the joint optimal coefficient of the BS and RIS. Then, the difference convex‐successive convex approximation based alternating optimization algorithm is proposed to solve this optimization problem. The simulation results show that the proposed scheme has improved 10‐bit/channel use compared with the randomization scheme of BS precoding and RIS reflection coefficient. It also has an improvement of 12‐bit/channel use compared with the spatially independent scheme.