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arXiv:2407.19960 · IEEE Transactions on Information Forensics and Security

Integrated Communications and Security: RIS-Assisted Simultaneous Transmission and Generation of Secret Keys

Ning Gao, Yuze Yao, Shi Jin, Cen Li, Michail Matthaiou

Published Jan 1, 2024• 11 citations
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Abstract

We develop a new integrated communications and security (ICAS) design paradigm by leveraging the concept of reconfigurable intelligent surfaces (RISs). In particular, we propose RIS-assisted simultaneous transmission and secret key generation by sharing the RIS for these two tasks. Specifically, the legitimate transceivers intend to jointly optimize the data transmission rate and the key generation rate by configuring the phase-shift of the RIS in the presence of a smart attacker. We first derive the key generation rate of the RIS-assisted physical layer key generation (PLKG). Then, to obtain the optimal RIS configuration, we formulate the problem as a secure transmission (ST) game and prove the existence of the Nash equilibrium (NE), and then derive the NE point of the static game. For the dynamic ST game, we model the problem as a finite Markov decision process and propose a model-free reinforcement learning approach to obtain the NE point. Particularly, considering that the legitimate transceivers cannot obtain the channel state information (CSI) of the attacker in real-world conditions, we develop a deep recurrent Q-network (DRQN) based dynamic ST strategy to learn the optimal RIS configuration. The details of the algorithm are provided, and then, the system complexity is analyzed. Our simulation results show that the proposed DRQN based dynamic ST strategy has a better performance than the benchmarks even with a partial observation information, and achieves “one time pad” communication by allocating a suitable weight factor for data transmission and PLKG.

DOI
10.1109/tifs.2024.3436885

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We develop a new integrated communications and security (ICAS) design paradigm by leveraging the concept of reconfigurable intelligent surfaces (RISs). In particular, we propose RIS-assisted simultaneous transmission and secret key generation by sharing the RIS for these two tasks. Specifically, the legitimate transceivers intend to jointly optimize the data transmission rate and the key generation rate by configuring the phase-shift of the RIS in the presence of a smart attacker. We first derive the key generation rate of the RIS-assisted physical layer key generation (PLKG). Then, to obtain the optimal RIS configuration, we formulate the problem as a secure transmission (ST) game and prove the existence of the Nash equilibrium (NE), and then derive the NE point of the static game. For the dynamic ST game, we model the problem as a finite Markov decision process and propose a model-free reinforcement learning approach to obtain the NE point. Particularly, considering that the legitimate transceivers cannot obtain the channel state information (CSI) of the attacker in real-world conditions, we develop a deep recurrent Q-network (DRQN) based dynamic ST strategy to learn the optimal RIS configuration. The details of the algorithm are provided, and then, the system complexity is analyzed. Our simulation results show that the proposed DRQN based dynamic ST strategy has a better performance than the benchmarks even with a partial observation information, and achieves “one time pad” communication by allocating a suitable weight factor for data transmission and PLKG.
We propose an integrated communications and security (ICAS) design paradigm that is RIS-assisted simultaneous transmission and secret key generation by sharing RIS for these two tasks. Specifically, the legitimate transceivers intend to jointly optimize the data transmission rate and the key generation rate by configuring the phase-shift of RIS in the presence of a smart attacker. We first derive the key generation rate of the RIS-assisted physical layer key generation (PLKG). Then, we model the problem as a finite Markov decision process and propose a model-free reinforcement learning approach to optimize the phase-shift of RIS. Particularly, due to the channel state information (CSI) of the attacker cannot obtain in real-world conditions, we develop a deep recurrent Q-network (DRQN) based dynamic ST strategy. Simulation results show that the proposed DRQN based dynamic ST strategy has a better performance than the benchmarks even with a partial observation information, and achieves “one time pad” communication by allocating a suitable weight factor for data transmission and PLKG.
By exploiting the entropy of wireless channels, physical layer key generation (PLKG) has gained considerable attention in recent years. Due to the characteristic of dynamic controlling of wireless channels, reconfigurable intelligent surface (RIS) can improve the key generation rate (KGR). Simultaneous transmission and reflection reconfigurable intelligent surface (STAR- RIS) can extend the half-space coverage to full-space coverage. This paper proposes a STAR-RIS-assisted physical layer key generation (SRKG) scheme in a multi-user case. The objective is to maximize the sum KGR by jointly designing the transmitting and reflecting coefficients (TARCs). We propose an iterative algorithm based on alternating optimization (AO), utilizing successive convex approximation (SCA) and semi-definite relaxation (SDR) methods, to solve the non-convex optimization problem in the presence of correlated channels. We also propose a low-complexity algorithm based on Lagrange multipliers to jointly optimize TARCs considering independent fading. Finally, the simulation results validate that, compared with the PLKG scheme assisted by traditional RIS (T-RIS), the proposed SRKG scheme can achieve higher sum KGR in a wider range under correlated and independent channel conditions.
Reconfigurable intelligent surface (RIS), which can manipulate the wireless environment, has recently been integrated into physical-layer key generation (PKG) systems to establish randomness symmetric keys in static environments. However, few studies have jointly considered the optimization and randomization of the RIS elements to simultaneously achieve a high key generation rate (KGR) and communication performance. This study proposes a RIS-assisted communication and security-integrated protocol for dual-function integration of communication enhancement and PKG in static environments. The protocol partitions RIS elements for beamforming and random beams for parallel execution, utilizing a sparsity adaptive matching pursuit-based channel estimation algorithm to obtain individual channel state information. Subsequently, an optimization problem is formulated for KGR maximization while satisfying quality of service (QoS) requirements. The non-convex optimization problem is addressed through monotonicity analysis and triangle inequality. We validate the efficacy of the proposed protocol by developing a 4.9 GHz RIS-assisted PKG prototype system, comprising modular hardware and flexible software. The field trials demonstrate a 30.81 bit/s KGR for static environments with an average received power increase of 10.6 dB, achieving effective simultaneous integration of communication and security.
The escalating demand for secure wireless communication, driven by the proliferation of connected devices, has made information security a paramount concern. Traditional encryption methods struggle against eavesdropping and malicious jamming in open wireless channels, necessitating innovative solutions. This paper explores physical layer security, leveraging intrinsic wireless channel properties, enhanced by reconfigurable intelligent surface (RIS). We propose an RIS-assisted multiple-input single-output system to counteract eavesdroppers and jamming threats through an artificial noise (AN) cooperation scheme. AN is injected during legitimate beamforming to bolster transmission security. Jointly optimizing the base station’s precoding vector, AN vector, and RIS reflection coefficients under power, quality, and phase constraints, we formulate a non-convex secrecy rate (SR) maximization problem. Addressing its complexity, we model it as a Markov decision process and develop a deep deterministic policy gradient algorithm within a deep reinforcement learning framework. Simulation results demonstrate the proposed method’s superior performance, reduced complexity, and robustness against multiple eavesdroppers and high-power jamming, underscoring the critical roles of RIS and AN in securing wireless communications. It consistently outperforms traditional algorithms such as alternating optimization with semidefinite programming, offering up to 7% higher SR and achieving nearly 120% SR gains as RIS elements scale from N =4 to N =10.
The potential of Reconfigurable Intelligent Surfaces (RISs) for energy-efficient and performance-boosted wireless communications is recently gaining remarkable research attention, motivating their consideration for various 5-th Generation (5G) Advanced and beyond applications. In this paper, we consider a Multiple-Input Multiple-Output (MIMO) Physical Layer Security (PLS) system with multiple data streams including one legitimate passive RIS and one malicious passive RIS, with the former being transparent to the multi-antenna eavesdropper and the latter’s presence being unknown at the legitimate multi-antenna transceivers. We first present a novel threat model for the RIS-boosted eavesdropping system and design a joint optimization framework for the eavesdropper’s receive combining matrix and the reflection coefficients of the malicious RIS. Focusing next on the secrecy rate maximization problem, we present an RIS-empowered PLS scheme that jointly designs the legitimate precoding matrix and number of data streams, the Artificial Noise (AN) covariance matrix, the receive combining matrix, and the reflection coefficients of the legitimate RIS. The proposed optimization algorithms, whose convergence to at least local optimum points is proved, are based on alternating maximization, minorization-maximization, and manifold optimization, including semi-closed form expressions for the optimization variables. Our extensive simulation results for two representative system setups reveal that, in the absence of a legitimate RIS, transceiver spatial filtering and AN are incapable of offering non-zero secrecy rates, even for malicious RISs with small numbers of elements. However, when anLLL-element legitimate RIS is deployed, confidential communication can be safeguarded against eavesdropping systems possessing even more than a5L5L5L-element malicious RIS.
A conventional secret key generation scheme achieves a low secret key rate in static environments. To solve this problem, the reconfigurable intelligent surface (RIS) antenna is merged with the device at the base station and is firstly proposed for secret key generation. By tuning the phase shifts at the RIS, a random varying beam can be generated and combined with the original wireless channel to form a new equivalent channel so that the key capacity is not subject to the time variance of the wireless channel. Then the closed-form solution is derived. Theoretical analysis and simulation show that the performance can be increased to that of a fast varying channel with limited radiating units. Moreover, the proposed scheme is superior to the existing schemes, in which the RIS is used as a reflective surface, over performance gain and preventing information disclosure. To further develop the gain of RIS, a joint design scheme is proposed, where some units are used for key generation, and some units are used for beamforming. Finally, the joint's closed-form solution scheme is derived. Finally, on the basis of satisfying the key capacity and communication performance, an optimal resource allocation strategy is proposed. Simulation results illustrate that the key capacity and communication performance can be improved simultaneously.