Secure Integrated Sensing and Communication Systems with the Assistance of Sensing Functionality

With the expectation of deeper integration between sensing and communication functionalities, we investigate the sensing-assisted approach to ensure the security of confidential information in Integrated Sensing and Communication (ISAC) systems. In physical layer security (PLS) studies, the acquisition of channel state information (CSI) is considered to be the common limitation. However, in ISAC systems, the sensing functionality is able to provide the channel information towards each target, aka., potential eavesdropper (Eve), by estimating the directions. In our design, the dual-functional base station (BS) emits an omnidirectional waveform, aiming to search for targets and obtain the angle estimations by employing the combined Capon and approximate maximum likelihood (CAML) technique. Afterwards, we formulate a weighted optimization problem with the help of artificial noise (AN) to jointly optimize the secrecy rate and the Cramér-Rao Bound (CRB), while generating a wide main-beam beampattern, covering all possible angles of the detected targets. By improving estimation accuracy, the sensing and security functionalities provide mutual benefits, resulting in improvement of the mutual performances with every iteration of the optimization, until convergence. Finally, the numerical results reveal the feasibility of the proposed algorithm and prove that it enables the multi-target scenario for secure ISAC systems.