In this paper, we investigate reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) systems for robust physical layer security (PLS) schemes. Traditionally, eavesdroppers (Eves) typically avoid interacting with the base station, making it challenging to obtain their relevant information, which limits the implementation of PLS. Fortunately, the sensing information obtained by ISAC can contribute to the design of PLS. Therefore, leveraging imperfect sensing estimation and employing dedicated radar signals as artificial noise, we formulate an RIS-assisted joint active and passive beamforming design problem to maximize the sum secrecy rate while satisfying the user’s quality of service constraints, the transmission power constraints, and the sensing signal strength requirements. To make the problem tractable, we first derive the bound for Eve’s channel state information uncertainty region based on security approximations. Subsequently, we employ the$\mathcal {S}$-procedure and the symbolic-deterministic methods to transform the infinite number of inequalities. We then utilize the first-order Taylor expansion, the second-order cone methods, and the successive convex approximation to address the nonconvexity problem, leading to an efficient suboptimal solution obtained by an iterative algorithm. Finally, the simulation results demonstrate the significant potential of the sensing function in enhancing security and the effectiveness of the proposed robust scheme in flexibly balancing communication and sensing quality.

Movable antennas (MAs) enhance flexibility in beamforming gain and interference suppression by adjusting position within certain areas of the transceivers. In this paper, we propose an MA-assisted integrated sensing and communication framework, wherein MAs are deployed for reconfiguring the channel array responses at both the receiver and transmitter of a base station. Then, we develop an optimization framework aimed at maximizing the sensing signal-to-interference-plus-noise-ratio (SINR) by jointly optimizing the receive beamforming vector, the transmit beamforming matrix, and the positions of MAs while meeting the minimum SINR requirement for each user. To address this nonconvex problem involving complex coupled variables, we devise an alternating optimization-based algorithm that incorporates techniques including the Charnes-Cooper transform, second-order Taylor expansion, and successive convex approximation (SCA). Specifically, the closed form of the received vector and the optimal transmit matrix can be first obtained in each iteration. Subsequently, the solutions for the positions of the transmit and receive MAs are obtained using the SCA method based on the second-order Taylor expansion. The simulation results show that the proposed scheme has significant advantages over the other baseline schemes. In particular, the proposed scheme has the ability to match the performance of the fixed position antenna scheme while utilizing fewer resources.

In this paper, we investigate physical layer security (PLS) for terrestrial RIS-assisted multibeam satellite commu-nications with similar channels. Deploying the reconfigurable intelligent surface (RIS) in each beam, and we use inter-beam in-terference and the channel variability from the RIS to the satellite user and eavesdroppers to enhance satellite security. Specifically, considering the constraints of the secrecy rate, we formulate a problem to minimize the total power by jointly optimizing the satellite beamforming and the RIS beamforming. To solve the problem, the original problem is decoupled into two non-convex optimization sub-problems, i.e., the active and the passive beamforming optimization problem. Then, semidefinite relax-ation (SDR) is used to solve the active beamforming optimization problem. The maximum ratio transmission-based beamforming and SDR are employed separately to solve passive beamforming optimization problem in each beam. The alternating optimization (AO) is utilized to solve the original problem and the convergence is proven. We have carried out simulations to evaluate the effectiveness of our proposed approach, the results show that the proposed algorithms have superior system performance.

The integration of nonorthogonal multiple access (NOMA) with integrated sensing and communication (ISAC) heralds a novel and promising paradigm, advancing the frontier of wireless communication technologies. Nevertheless, this synergistic integration may confront security challenges attributable to intrinsic vulnerabilities within the ISAC frameworks, i.e., sensing targets assume the role of potential eavesdroppers. In this article, we exploit the additional degrees of freedom afforded by reconfigurable intelligent surfaces (RISs) to enhance secure communication and achieve target detection within the NOMA-assisted ISAC system. Specifically, the coexisting radar and NOMA signals are concurrently propagated through both the direct and reflected links. Subsequently, we formulate a secure optimization problem by collaboratively designing the beamforming vectors of the base station and the phase shifts of RIS under the constraints of total transmit power, communication quality of service, and sensing quality. Due to nonconvexity, the optimization problem is decomposed into two subproblems and addressed separately, employing the successive convex approximation approach based on the first-order Taylor expansion and the second-order cone. Finally, we obtain the solution to the original problem utilizing alternating optimization. Simulation results demonstrate that our proposed approach exhibits superior capabilities in secure communication and precise target detection.