# Secure Beamforming Design for UAV-Empowered Integrated Sensing and Communication
###### Abstract  
Integrated sensing and communication (ISAC) systems assisted by unmanned aerial vehicles (UAVs) are susceptible to eavesdropping, making secure information transmission a critical area of research. We propose a joint optimization algorithm to improve the security of UAV-assisted ISAC systems through coordinated adjustments of transmit beamforming and UAV position. The optimization problem aims to minimize the maximum eavesdropping signal-to-interference-plus-noise ratio (SINR) across multiple legitimate users while adhering to three distinct constraints: service quality for legitimate users, sensing requirements for detecting eavesdroppers, and limitations on system transmit power. To address the non-convex optimization challenge effectively, the problem is decomposed into sub-problems focusing on the optimization of transmit beamforming and UAV position. These sub-problems are solved using semidefinite relaxation (SDR), the Dinkelbach method, and successive convex approximation (SCA), with iterative alternation achieving optimal values for the transmit beamforming and UAV position while also proving the convergence of the algorithm. Lastly, simulation results illustrate that the proposed algorithm markedly improves the system's security performance while preserving its communication and sensing capabilities. Keywords:integrated sensing and communication; multi-antenna beamforming; physical layer security +
Footnote †: journal: Applied
entailed adjustments to the transmitting beamforming of the multi-antenna base station and the phase shifts of the RIS. Due to the significant strides made in UAV technology, they have become a highly promising aerial platform within ISAC systems, offering new solutions to overcome the limitations of traditional ground networks. The introduction of highly mobile and flexible UAVs enables ISAC systems to exhibit superior performance in specific scenarios. Optimization challenges for UAVs in both hovering and flying states were explored, with a focus on the joint design of UAV trajectories and beamforming weights to enhance the ISAC system's performance [11]. Considering the potential impact of sensed signal reception on the communication signal-to-noise ratio, a time-division sensing mechanism was proposed [12]. This mechanism allows the flexible allocation of UAV sensing times, enabling sensing and communication to occur non-simultaneously. By jointly optimizing UAV flight trajectories, beamforming weights, and user reception weights, the communication performance of the system has been further enhanced. In the aforementioned system, UAVs act as base stations. In [13], UAVs were utilized as relays, with the information age serving as a performance metric. The research minimized this metric by alternately optimizing UAV trajectories, transmit power, and service times, thereby enhancing communication and sensing coverage, as well as overall ISAC system performance. A multi-UAV-assisted ISAC system, where UAVs transmit information to moving ground users while simultaneously sensing them [14]. In [15], the deployment of multiple UAVs to transmit dual-function signals for both communication and location tracking of ground users was discussed. In contrast to [14], this study utilized an extended Kalman filter to accurately estimate and predict the time delays and Doppler shifts in the reflected signals from targets, which ensures precise target tracking. As ISAC systems rapidly evolve, although their communication and sensing capabilities are increasingly robust, the openness of wireless communication media has raised security concerns, particularly regarding the physical layer security (PLS) of ISAC systems [16]. Artificial noise (AN) is utilized to disrupt eavesdroppers, aiming to maximize the power of AN given that the base station is unaware of the eavesdropper's channel state, which hinders eavesdropping while maintaining robust communication and sensing performance [17; 18].