Sensing-Assisted Secure Beamforming for RIS-Enabled ISAC with Leakage Suppression

Reconfigurable intelligent surface (RIS)-enabled integrated sensing and communication (ISAC) is emerging as a key 6G technology for improving spectral efficiency and enabling high-resolution sensing. However,sensing targets within the communication coverage may act as potential eavesdroppers and intercept confidential data. To address this challenge, this paper proposes a sensing-assisted secure beamforming framework to enhance physical-layer security (PLS). First, we design a closed-loop architecture that sequentially performs RIS cascaded CSI estimation, target direction-of-arrival (DoA) estimation, and a Cramér-Rao bound (CRB)-based sensing accuracy evaluation. We then introduce an angular-domain information leakage (ADIL) metric to characterize leakage within the target's angular uncertainty region. Building on this metric, we formulate a weighted-sum utility to jointly optimize the communication rate and sensing CRB under an ADIL-suppression constraint. To solve the resulting non-convex problem, we develop a penalty dual decomposition (PDD)-augmented alternating optimization (AO) algorithm that iteratively updates the BS beamforming, RIS phase shifts, and sensing time allocation. Convergence and complexity analyses further demonstrate that PDD accelerates AO convergence and mitigates zig-zag updates caused by coupled variables. Simulation results verify that the proposed sensing-assisted secure beamforming scheme effectively suppresses ADIL at eavesdropper angles and enhances PLS. Moreover, the PDD-augmented AO achieves up to a 21.3% improvement in communication rate and a 5.2% reduction in CRB compared with conventional schemes.