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IEEE Transactions on Vehicular Technology

Secure Integrated Communications and Sensing Using Physical Layer Key Generation

Kexin Liu, Kaizhi Huang, Zheng Chu, Xiaoyan Hu, Liang Jin, Feihu Wang, Xinglong Pei

Published Mar 6, 2026• 0 citations
Publisher

Abstract

To establish a secure integrated communications and sensing (ISAC) system, this paper proposes a physical layer key generation (PLKG) scheme coupled to the ISAC characteristics. Firstly, we propose a novel PLKG protocol and formulate a sum secret key rate maximization problem under the sensing accuracy by jointly optimizing the communication and sensing beamforming. To address the complex optimization problems, a proximal policy optimization (PPO)-based reinforcement learning (RL) algorithm is proposed. Simulation results demonstrate the effectiveness and superiority of the proposed PPO-based RL algorithm compared to the benchmark schemes.

DOI
10.1109/tvt.2026.3671132

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To establish a secure integrated communications and sensing (ISAC) system, this paper proposes a physical layer key generation (PLKG) scheme coupled to the ISAC characteristics. Firstly, we propose a novel PLKG protocol and formulate a sum secret key rate maximization problem under the sensing accuracy by jointly optimizing the communication and sensing beamforming. To address the complex optimization problems, a proximal policy optimization (PPO)-based reinforcement learning (RL) algorithm is proposed. Simulation results demonstrate the effectiveness and superiority of the proposed PPO-based RL algorithm compared to the benchmark schemes.
Integrated Sensing and Communication (ISAC) can reuse the same spectrum and hardware resources for communication and radar sensing, which is a promising technology to alleviate spectrum congestion. Recently, there has been an increasing research interest in the physical layer secrecy aspects of ISAC systems. This paper studies a basic multiple-input single-output ISAC secrecy system, where a multi-antenna base station transmits a unified signal to sense a point target and communicate to a single-antenna receiver in the presence ofKKKsingle antenna eavesdroppers. Under this setup, a sensing signal-to-noise ratio (SNR) constrained secrecy rate maximization problem has been formulated. We showed that the problem can be reformulated as a convex semidefinite programming problem and proved that beamforming is the optimal transmission scheme. We derived two low-complexity semiclosed-form optimal beamforming solutions and one suboptimal closed-form solution. Numerical results demonstrate that the proposed solutions attain the optimum of the sensing SNR constrained secrecy rate maximization problem and have lower computational complexity than the existing method.
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.
Empowered by the integrated sensing and communication capability, this paper proposes a new two-stage artificial noise (AN)-assisted secure beamforming design towards physical layer security enhancement. Specifically, in the first stage a nearly omni-directional AN is used for sensing the eavesdropper, where the AN is radiated istropically except in the direction of the communication user. With the known channel knowledge of the eavesdropper, a spatially AN is transmitted in the second stage to deliberately degrade the eavesdropper. To balance the sensing and secure communication performance, we aim to maximize the effective secrecy rate by jointly optimize the time allocation and the transmit beamforming in both stages. A efficient optimization algorithm based on weighted minimum mean square error is then developed to solve the formulated non-convex problem. Simulation results are provided to demonstrate the performance advantage of our proposed design over the existing benchmark schemes in terms of achieving a larger effective secrecy rate.
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.
This paper develops a two-phase secure integrated sensing and communication (ISAC) framework, where a dual-functional transmitter (Alice) detects the existence of a potential eavesdropper (Eve) as a sensing target in the first phase. In the second phase, Alice adapts her secure transmission strategy based on the sensing outcome of the first phase. A distinct aspect of our proposed two-phase framework is the derivation of the overall effective secrecy rate across both phases. This is achieved by seamlessly incorporating the a priori probability of Eve’s presence, the sensing false alarm rate, and the sensing detection probability directly into the effective secrecy rate as weighting coefficients. For system design, we aim to maximize the overall effective secrecy rate subject to Alice’s average transmit power remaining below a predetermined threshold. To address the resulting non-convex design problem, an algorithm based on semi-definite relaxation (SDR) and double-layer optimization is proposed. Our numerical results show that the proposed two-phase secure ISAC framework significantly enhances the secrecy rate compared to a conventional physical layer security (PLS) system if Eve is present with a low probability.
This paper studies the joint secure transceiver design for the full-duplex integrated sensing and communication (ISAC) system, in which the base station performs the target tracking and communicates with the downlink and the uplink users by reusing the resources. Here, the target, referred to as Eve, is a potential eavesdropper with the intention of intercepting both the downlink and the uplink information. The security problem of the full-duplex ISAC system has not been studied well, where the sensing and communication signals suffer from the serious interference. In this paper, we jointly design the information beamformer, the radar waveform, the uplink communication receive filter, and the radar receive filter to achieve the downlink and uplink communication security and the target tracking. Specifically, both the Eve’s signal-to-interference-plus-noise ratio minimization and the secrecy rate maximization problems, subject to the sensing and the communication constraints, are formulated for the ISAC system from the perspectives of the quality of service and the secrecy rate. An iterative algorithm is proposed for solving the formulated problems. We prove that, under appropriate conditions, the proposed iterative algorithm converges to the Karush-Kuhn-Tucker optimal point of the original problem without the rank 1 constraint. We further extend the joint design to the case of the imperfect wiretap channel and the angle uncertainty. Numerical results show that our scheme remarkably outperforms the benchmark approaches. The performance is close to that of designing the secure communication and the sensing separately.