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Impact of reconfigurable intelligent surfaces on physical layer key generation in NextG wireless networks

Guyue Li, Lei Hu, Long Jiao, Kai Zeng, Chen Sun, Aiqun Hu

Published Apr 23, 2024• 0 citations
Publisher

Abstract

Physical layer key generation (PKG) is a promising means to provide on-the-fly shared secret keys by exploiting the intrinsic randomness of the radio channel. However, the performance of PKG is highly dependent on the wireless propagation environment. Due to its feature of controlling the wireless environment, reconfigurable intelligent surface (RIS) is appealing to be applied in PKG. In this chapter, we explore the effects of RIS on PKG from both constructive and destructive perspectives. For the constructive aspect, we have identified static and wave-blockage environments as two RIS-empowered-PKG applications in future wireless systems. Furthermore, we also point out that RIS could be utilized by an attacker to perform new jamming and leakage attacks and provide countermeasures, respectively. At last, possible directions for future research have also been given.

DOI
10.1049/pbte107e_ch9

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Physical layer key generation (PKG) is a promising means to provide on-the-fly shared secret keys by exploiting the intrinsic randomness of the radio channel. However, the performance of PKG is highly dependent on the wireless propagation environment. Due to its feature of controlling the wireless environment, reconfigurable intelligent surface (RIS) is appealing to be applied in PKG. In this chapter, we explore the effects of RIS on PKG from both constructive and destructive perspectives. For the constructive aspect, we have identified static and wave-blockage environments as two RIS-empowered-PKG applications in future wireless systems. Furthermore, we also point out that RIS could be utilized by an attacker to perform new jamming and leakage attacks and provide countermeasures, respectively. At last, possible directions for future research have also been given.
Physical layer key generation (PKG) is a promising means to provide on-the-fly shared secret keys by exploiting the intrinsic randomness of the radio channel. However, the performance of PKG is highly dependent on the propagation environments. Due to its feature of controlling the wireless environment, reconfigurable intelligent surface (RIS) is appealing to be applied in PKG. In this article, in contrast to the existing literature, we investigate both the constructive and destructive effects of RIS on the PKG scheme. For the constructive aspect, we have identified static and wave-blockage environments as two RIS-empowered-PKG applications in future wireless systems. In particular, our experimental results in a static environment showed that RIS can enhance the entropy of the secret key, achieving a key generation rate (KGR) of 97.39 bit/s with a bit disagreement rate (BDR) of 0.083. In multi-user systems where some remote users are in worse channel conditions, the proposed RIS-assisted PKG algorithm improves the sum secret key rate by more than 2 dB, compared to the literature. Furthermore, we point out that RIS could be utilized by an attacker to perform new jamming and leakage attacks and give countermeasures, respectively. Finally, we outline future research directions for PKG systems in light of the RIS.
Physical layer key generation (PLKG) is a promising technology to obtain symmetric keys between a pair of wireless communication users in a plugand- play manner. The shared entropy source almost entirely comes from the intrinsic randomness of the radio channel, which is highly dependent on the wireless environments. However, in some static/ block fading wireless environments, it is hard to guarantee the intrinsic randomness of the wireless channel. Thanks to reconfigurable intelligent surfaces (RISs) with their excellent ability on electromagnetic wave control, the wireless channel environment can now be customized. In this article, we overview the RIS-aided PLKG in static indoor environments, including its channel model and hardware architectures. Then we propose potential application scenarios and analyze the design challenges of RIS-aided PLKG, including channel reciprocity, RIS reconfiguration speed, and RIS deployment via proof-of-concept experiments on a RIS-aided PLKG prototype system. In particular, our experimental results show that the key generation rate is 15-fold higher than that without RIS in a static indoor environment. Next, we design a RIS jamming attack via a prototype experiment and discuss its possible attack-defense countermeasures. Finally, several conclusions and future directions are identified.
Due to the capability of controlling wireless environments, reconfigurable intelligent surface (RIS) can be exploited to assist radio channel-based physical-layer key generation (PKG). However, this may also pose great security threats to PKG when it is controlled by an attacker. To this end, this letter studies a RIS leakage (RISL) attack that assists the attacker to manipulate the generated keys between the legitimate ends in PKG systems. Specifically, in block fading environments, by alternatingly adapting the RIS reflection coefficients to all 0s and 1s in each block, the received signal strength (RSS) at the legitimate ends is likely to be boosted and attenuated regularly across time, causing predictable 0s and 1s in the quantized bits. To resist this attack, we propose a countermeasure based on dynamic private pilots (CDPP) and prove that the RISL success probability can be significantly reduced by CDPP. Simulation results verify the effectiveness of the proposed attack and countermeasure, highlighting the importance of introducing artificial randomness for secret key security in block fading channels.
This paper presents an optimal shifting scheme using reconfigurable intelligent surfaces (RIS) to aid physicallayer key generation (PKG) and enhance communication and key generation rate (KGR) in static environments. Our approach involves designing a protocol for RIS-aided key generation and optimizing RIS coefficients to introduce phase randomization in the wireless channel while maximizing power reception. Simulation results demonstrate the effectiveness of our proposed protocol in improving both communication performance and KGR under static conditions.
This paper proposes a reconfigurable intelligent surface (RIS) assisted physical layer key generation (PKG) scheme to increase the key generation rate (KGR). Firstly, we provide a high-rate key generation protocol that rapidly and randomly switches the phase of RIS elements. Then, we analyze the key information leaked to passive eavesdroppers and give the closed-form expression of KGR when the number of RIS elements is sufficiently large. Monte Carlo simulation and numerical results show that our proposed scheme can boost KGR in a static environment.
Reconfigurable intelligent surfaces (RIS) have the ability to alter the wireless environment by making changes in the impinging signal. While RIS has been extensively studied for enhancing wireless communications, its potential for facilitating group key generation (GKG) remains unexplored. In this study, we exploit the RIS to make the aggregate reflecting channels of different user terminals (UTs) as similar as possible to be able to extract common group secret keys from their channels. Specifically, the RIS will adjust its parameters to pave the way for GKG based on the physical channels of the UTs. Our method exploits the already gathered channel state information (CSI) in the RIS to beneficially design the phase shifts and does not impose additional probing burden on the network. We consider both passive RIS (PRIS) and active RIS (ARIS) to generate the group keys. The PRIS is widely adopted in physical layer key generation (PLKG) studies due to its use of passive elements, whereas the ARIS demonstrates superior capability in aligning the aggregate reflected channels among nodes in the GKG scenario, as demonstrated in this study. We will exploit various optimization methods like successive convex approximation (SCA) and semidefinite relaxation with Gaussian randomization (SDR-GR) to address the raised optimization problems. Unlike most of the studies in the literature, our scheme can achieve a high GKG rate in static environments as well. Finally, we will examine the performance of the proposed method by normalized mean squared error (NMSE), key error rate (KER), key generation rate (KGR) and key randomness metrics. Our numerical results verify that for the equal available power budget, the ARIS significantly outperforms PRIS in NMSE and KER, achieving more than four times higher KGR.