Integrated Sensing and Communication (ISAC) systems vulnerability to information interception has become more dramatic with the usage of unified signaling techniques. This paper introduces a secure full-duplex (FD) multi-eavesdroppers (Eve) ISAC system, where malicious users, termed as Eve, aim at intercepting the downlink (DL) as well as the uplink (UL) information interchanged between legitimate DL/UL users and the dual functional radar and communication (DFRC) base station (BS). Following the model, we design a suitable secure ISAC method that invests minimal power in the FD system in order to satisfy desired UL/DL secrecy rates, while illuminating radar beams at Eves. The motivation being that the FD system should expose minimal useful information towards the Eves, while simultaneously sensing their physical parameters. To this end, a suitable optimization problem is formed taking into account the aforementioned requirements, and a successive convex approximation approach is taken to iteratively solve the problem. Simulation results also reveal secrecy-sensing trade-offs and demonstrate the effectiveness of the method for different system parameters and requirements.
Integrated Sensing and Communication (ISAC) systems vulnerability to information interception has become more dramatic with the usage of unified signaling techniques. This paper introduces a secure full-duplex (FD) multi-eavesdroppers (Eve) ISAC system, where malicious users, termed as Eve, aim at intercepting the downlink (DL) as well as the uplink (UL) information interchanged between legitimate DL/UL users and the dual functional radar and communication (DFRC) base station (BS). Following the model, we design a suitable secure ISAC method that invests minimal power in the FD system in order to satisfy desired UL/DL secrecy rates, while illuminating radar beams at Eves. The motivation being that the FD system should expose minimal useful information towards the Eves, while simultaneously sensing their physical parameters. To this end, a suitable optimization problem is formed taking into account the aforementioned requirements, and a successive convex approximation approach is taken to iteratively solve the problem. Simulation results also reveal secrecy-sensing trade-offs and demonstrate the effectiveness of the method for different system parameters and requirements.
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.
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.
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 paper, we study the robust secure unmanned aerial vehicle (UAV) communication system, where a UAV with full-duplex (FD) capability simultaneously receives the information signal from a ground unit (GU) and transmits jamming signal to degrade the wiretap capability of potential multiple ground eavesdroppers (Eves). With the consideration of estimation error of Eves' locations, we aim to maximize the average worst secrecy rate inside a certain flight period of the UAV by jointly optimizing the transmit power of the GU and UAV as well as the trajectory of the UAV. The resulting problem is intractable due to its non-convex nature and strongly coupled variables. Furthermore, the estimation error of Eves' locations results in an infinite number of constraints, which makes the problem even more difficult. To tackle this difficulty, we first propose an iterative algorithm based on the Schur complement lemma and successive inner approximation method to efficiently solve the problem suboptimally under the estimated Eves' locations. Then, in order to cope with the of Eves' location errors, we develop a cutting-set method, which solves the problem by alternating between optimal power-trajectory design and worst-case Eves' locations analysis. Via simulation, we show the improvement of the proposed algorithm compared to other benchmark algorithms under high FD self-interference cancellation levels.
In this paper, we investigate resource allocation for a multiuser communication system employing a full-duplex base station for serving multiple half-duplex downlink and uplink users simultaneously. The considered system enables secure simultaneous downlink and uplink communication via artificial noise (AN) generation causing interference to potential eavesdroppers. The system design objective is to maximize the system secrecy throughput by jointly optimizing the downlink beamformer, the AN covariance matrix, and the uplink transmit power. The algorithm design leads to a non-convex optimization problem and obtaining the globally optimal solution entails a prohibitively high computational complexity. Therefore, an efficient suboptimal iterative algorithm based on successive convex approximation is proposed. Our simulation results confirm that the proposed suboptimal algorithm achieves a substantial system secrecy throughput gain compared to two baseline schemes.
This paper investigates secure beamforming design for simultaneous proactive eavesdropping and communication in a multiuser multi-antenna system, where a full-duplex base station (FD-BS) serves multiple legitimate users, monitors a suspicious link, and suppresses multiple eavesdroppers. The proposed design is formulated as maximizing the weighted sum secrecy rate (WSSR) of legitimate users, subject to a total transmit-power requirement and a proactive eavesdropping constraint. The initial problem is hard to solve due to the high non-convexity of the objective function and the proactive eavesdropping constraint. By introducing three auxiliary variables, the original WSSR maximization problem is equivalently reformulated as a weighted minimum mean square error (WMMSE) minimization problem. The reformulated WMMSE minimization problem remains non-convex, where a block coordinate descent (BCD) algorithm based on first-order Taylor approximation is proposed to solve it iteratively. Aiming to reduce the computational complexity of the proposed method, a low complexity zero-forcing beamforming algorithm is designed. Simulation results demonstrate that the proposed algorithms can achieve superior trade-offs among communication efficiency, secrecy enhancement, and surveillance performance than conventional methods.