Secret key generation in physical layer security exploits the unpredictable random nature of wireless channels. The millimeter-wave (mmWave) channels have limited multipath and channel randomness in static environments. In this paper, for mmWave secret key generation of physical layer security, we use a reconfigurable intelligent surface (RIS) to induce randomness directly in wireless environments, without adding complexity to transceivers. We consider RIS to have continuous individual phase shifts (CIPS) and derive the RIS-assisted reflection channel distribution with its parameters. Then, we propose continuous group phase shifts (CGPS) to increase the randomness specifically at legal parties. Since the continuous phase shifts are expensive to implement, we analyze discrete individual phase shifts (DIPS) and derive the corresponding channel distribution, which is dependent on the quantization bit. We then derive the secret key rate (SKR) to evaluate the randomness performance. With the simulation results verifying the analytical results, this work explains the mathematical principles and lays a foundation for future mmWave evaluation and optimization of artificial channel randomness.
Secret key generation in physical layer security exploits the unpredictable random nature of wireless channels. The millimeter-wave (mmWave) channels have limited multipath and channel randomness in static environments. In this paper, for mmWave secret key generation of physical layer security, we use a reconfigurable intelligent surface (RIS) to induce randomness directly in wireless environments, without adding complexity to transceivers. We consider RIS to have continuous individual phase shifts (CIPS) and derive the RIS-assisted reflection channel distribution with its parameters. Then, we propose continuous group phase shifts (CGPS) to increase the randomness specifically at legal parties. Since the continuous phase shifts are expensive to implement, we analyze discrete individual phase shifts (DIPS) and derive the corresponding channel distribution, which is dependent on the quantization bit. We then derive the secret key rate (SKR) to evaluate the randomness performance. With the simulation results verifying the analytical results, this work explains the mathematical principles and lays a foundation for future mmWave evaluation and optimization of artificial channel randomness.
Physical-layer key generation (PLKG) can significantly enhance the security of classic encryption schemes by efficiently providing secret keys in resource-limited network like the Internet of Things (IoT). However, reaching a high key generation rate (KGR) is challenging in applications like smart home or remote area sensing with quasi-static channels. Recently, exploiting reconfigurable intelligent surface (RIS) to induce randomness in quasi-static wireless channels has received significant research interest. However, the inherent spatial correlation among the RIS elements is rarely studied, which can alter the optimum physical-layer key generation (PLKG) approach in terms of KGR and randomness in the key sequence. Specifically, for the first time, in this contribution, we take into account a spatially correlated RIS, which intends to enhance the KGR in a quasi-static medium. Novel closed-form analytical expressions for KGR are derived for the two cases of random phase shift (RPS) and our proposed equal phase shift (EPS) in the RIS elements. We also analyze the correlation between the channel samples to ensure the randomness of the generated secret key sequence. It is shown that the EPS scheme can effectively exploit the inherent spatial correlation between the RIS elements and it leads to a higher KGR compared to the widely used RPS strategy. We further formulate an optimization problem in which we determine the optimal portion of time dedicated to direct and indirect channel estimation, which has never been addressed in previous studies. We show the accuracy and the fast convergence of our sequential convex programming (SCP)-based algorithm and discuss the various parameters affecting spatially correlated RIS-assisted PLKG.
Physical layer key generation (PLKG) is a promising method to generate secret keys by harnessing the randomness of wireless channels. In this letter, a reconfigurable intelligent surface (RIS)-assisted multi-carrier PLKG framework is proposed to overcome the lack of channel randomness in static environments. Specifically, the secret key generation rate (SKGR) is analyzed based on the inter-frequency correlation among the channel coefficients across subcarriers. Building upon this analysis, a novel scheme for configuring RIS elements is proposed to enhance the SKGR by introducing correlations into the random phase shifts of RIS elements. Simulation results are presented to validate the effectiveness of the proposed scheme.
Key generation, a pillar in physical-layer security (PLS), is the process of the exchanging signals from two legitimate users (Alice and Bob) to extract a common key from the random, common channels. The drawback of extracting keys from wireless channels is the ample dependence on the dynamicity and fluctuations of the radio channel, rendering the key vulnerable to estimation by Eve (an illegitimate user) in low-entropy environments because of insufficient randomness. Added to that, the lack of channel fluctuations lower the secret key rate (SKR) defined as the number of bits of key generated per channel use. In this work, we aim to address this challenge by using a reconfigurable intelligent surface (RIS) to produce random phases at certain, carefully curated intervals such that it disrupts the channel in low-entropy environments. We propose an RIS assisted key generation protocol, study its performance, and compare with benchmarks to observe the benefit of using an RIS while considering various important metrics such as key mismatch rate and secret key throughput. Furthermore, we characterize a scaling law as a function of the rate of change of RIS phase switching for the average secret information rate under this protocol. Then, we use both the key throughput and information rate to optimize the overall secrecy rate. Simulations are made to validate our theoretical findings and effectiveness of the proposed scheme showing an improvement in performance when an RIS is deployed.
Physical-layer security (PLS) is superior to classical cryptography techniques due to its notion of perfect secrecy and independence to an eavesdropper's computational power. One form of PLS arises when Alice and Bob (the legitimate users) exchange signals to extract a common key from the random common channels. The drawback of extracting keys from wireless channels is the ample dependence on the dynamicity and fluctuations of the radio channel. However, some radio channels are constant such as line-of-sight (LoS) and can be estimated by Eve (an illegitimate user), or can be quite static in behavior due to the presence low-mobility users thus restricting the amount of randomness. This in turn lowers the secret key rate (SKR) defined as the number of bits of key generated per channel use. In this work, we aim to address this challenge by using a reconfigurable intelligent surface (RIS) to produce random phases at certain carefully curated intervals such that it disrupts the channel in low-entropy environments. We propose an RIS assisted key generation method, study its performance, and compare with benchmarks to observe the benefit of using an RIS while considering various important metrics such as key mismatch rate and average secret key throughput. Simulations are made to validate our theoretical findings showing an improvement in performance when an RIS is deployed.
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.
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.