The integrated sensing and communication (ISAC) gives the new paradigm for the secure communication design. In this paper, the dual-functional radar communication (DFRC) enabled physical layer security (PLS) is investigated. Specifically, we propose the novel Cramér-Rao bound (CRB) based statistical imperfect channel state information (CSIC) model, which integrates the radar CRB into the statistical imperfect CSI model based on the second-order moment. Further, the CSIC based PLS optimization model is proposed, where the expectation of the secrecy rate is maximized under the PLS requirement and the radar CRB based constraint. The corresponding CSIC semidefinite relaxation (CSIC-SDR) based iteration algorithm is developed to achieve the beamforming design with the aid of one-dimension search of the optimal CRB based sensing measure. Numerical results demonstrate that the proposed CSIC-SDR outperforms the norm-bound CSI based and circularly symmetric complex Gaussian distribution CSI based beamforming designs in terms of the PLS performance.
The integrated sensing and communication (ISAC) gives the new paradigm for the secure communication design. In this paper, the dual-functional radar communication (DFRC) enabled physical layer security (PLS) is investigated. Specifically, we propose the novel Cramér-Rao bound (CRB) based statistical imperfect channel state information (CSIC) model, which integrates the radar CRB into the statistical imperfect CSI model based on the second-order moment. Further, the CSIC based PLS optimization model is proposed, where the expectation of the secrecy rate is maximized under the PLS requirement and the radar CRB based constraint. The corresponding CSIC semidefinite relaxation (CSIC-SDR) based iteration algorithm is developed to achieve the beamforming design with the aid of one-dimension search of the optimal CRB based sensing measure. Numerical results demonstrate that the proposed CSIC-SDR outperforms the norm-bound CSI based and circularly symmetric complex Gaussian distribution CSI based beamforming designs in terms of the PLS performance.
This paper considers transmit beamforming in dual‐function radar‐communication (DFRC) system, where a DFRC transmitter simultaneously communicates with a communication user and detects a malicious target with the same waveform. Since the waveform is embedded with information, the information is risked to be intercepted by the target. To address this problem, physical‐layer security technique is exploited. By using secrecy rate and estimation rate as performance measure for communication and radar, respectively, three secrecy rate maximization (SRM) problems are formulated, including the SRM with and without artificial noise (AN) and robust SRM. For the SRM beamforming, we prove that the optimal beamformer can be computed in closed form. For the AN‐aided SRM, by leveraging alternating optimization, similar closed‐form solution is obtained for the beamformer and the AN covariance matrix. Finally, the imperfect CSI of the target is also considered under the premise of a moment‐based random phase‐error model on the direction of arrival at the target. Simulation results demonstrate the efficacy and robustness of the proposed designs.
The following paper models a secure full duplex (FD) integrated sensing and communication (ISAC) scenario, where malicious eavesdroppers aim at intercepting the downlink (DL) as well as the uplink (UL) information exchanged between the dual functional radar and communication (DFRC) base station (BS) and a set of communication users. The DFRC BS, on the other hand, aims at illuminating radar beams at the eavesdroppers in order to sense their physical parameters, while maintaining high UL/DL secrecy rates. Based on the proposed model, we formulate a power efficient secure ISAC optimization framework design, which is intended to guarantee both UL and DL secrecy rates requirements, while illuminating radar beams towards eavesdroppers. The framework exploits artificial noise (AN) generation at the DFRC BS, along with UL/DL beamforming design and UL power allocation. We propose a beamforming design solution to the secure ISAC optimization problem. Finally, we corroborate our findings via simulation results and demonstrate the feasibility, as well as the superiority of the proposed algorithm, under different situations. We also reveal insightful trade-offs achieved by our approach.
The channel state information (CSI) of malicious users in the field of physical layer security is usually difficult to obtain due to the users’ passive listening. However, as sensing is integrating into the cellular network, it becomes feasible to acquire the CSI of passive eavesdroppers. Motivated by this, we propose a novel sensing-aided secure communication (SASC) scheme in this paper, which is implemented by a two-stage transmission protocol including beam sensing of the eavesdropper’s CSI and secure communication to the legitimate user against the eavesdropper. In the first stage, the base station (BS) needs to decide the number of sensing beamsL, and we derive the closed-form Cramer-Rao bound (CRB) to establish the relationship between the estimated angle range for the eavesdropper’s location andL, where a largerLfor beam sensing returns a tighter CRB to locate the eavesdropper. In the second stage, the BS designs the beamforming vector to transmit confidential data to the legitimate user and avoid leakage to the eavesdropper in the estimated range. As sensing affects the subsequent secure communication, we decouple the non-convex two-stage joint optimization problem into two subproblems and solve it by backward induction. In particular, in the secrecy beamforming subproblem givenL, we investigate the worst-case information leakage by constructing a convex hull to approximate the angle range from sensing. Then we develop a semi-closed-form solution of robust secrecy beamforming vector, and use it for the other subproblem to decide initialL. To achieve this goal, we also obtain a semi-closed-form solution ofLby considering all potential estimated results in the worst case. Finally, we present simulation results to show the effectiveness and robustness of the proposed SASC scheme as compared to various benchmarks.
Physical layer security (PLS) has emerged as a promising technology to protect critical and sensitive information against unauthorized devices. To address the key challenge of acquiring channel state information (CSI) of passive eavesdroppers in PLS implementation, we propose a novel sensing-assisted PLS scheme with the aid of reflecting reconfigurable intelligent surface (STAR-RIS). It employs a self-refine sensing scheme utilizing the artificial noise (AN) signals to iteratively estimate the eavesdroppers’ positions for CSI calculation. We aim to maximize the secrecy capacity based on the sensing-estimated CSI while tracking the eavesdroppers in full-duplex (FD) mode with integrated sensing and communication (ISAC) signals comprising artificial noise (AN). This is achieved by jointly designing the beamforming vector of information signals, the beamforming vector of AN signals, and the coefficients of the STAR-RIS. To optimize these coupled variables, we introduce an alternating optimization (AO) scheme to solve the problem recursively. In particular, we tackle the non-convexity of the beamforming optimizations for information and AN signals with the successive convex approximation (SCA) scheme and adopt a semi-definite relaxation (SDR) scheme to design the reflection and refraction coefficients of the STAR-RIS. The numerical results validate that the proposed scheme ensures secure communications against multiple eavesdroppers without any prior eavesdropper channel information. In addition, the proposed scheme can significantly improve SC performance by up to 66. 7% compared to the benchmarks without the sensing-assisted function.
In this letter, we propose a near-field secure integrated sensing and communication (ISAC) system architecture, where the ISAC system simultaneously performs target detection and tracking while transmitting communication information to downlink users. However, in the presence of malicious eavesdropping devices, the security of communication transmission in ISAC systems cannot be guaranteed. Near-field effects introduce an additional advantage in the distance dimension, which improves the accuracy of target distance and angle estimation. Simultaneously, beamforming can be spatially focused at specific points to prevent information leakage. Motivated by these benefits, We construct a weighted optimization framework aimed at jointly maximizing the overall secrecy rate and reducing the Cramér-Rao Bound (CRB) for target estimation in near-field scenarios, while adhering to communication demands and total power limitations of the system. By integrating fractional programming (FP) and semidefinite relaxation (SDR) techniques, we jointly optimize the transmit waveform covariance matrix and the beamforming vectors to enhance both sensing accuracy and secure transmission performance simultaneously. Numerical results reveal that the secure near-field ISAC scheme can effectively achieve a synergy enhancement between sensing and secure communication while maintaining reliable system performance.
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.