  In dual-function radar-communication (DFRC) systems the probing signal
contains information intended for the communication users, which makes that
information vulnerable to eavesdropping by the targets. We study the security
of a DFRC system aided by an intelligent reflecting surface (IRS) from the
physical layer security (PLS) perspective. The IRS helps overcome path loss or
blockage and introduces more degrees of freedom for system design, however, it
also makes the design problem more challenging. In the system considered, the
radar embeds artificial noise (AN) in the probing waveform, and the radar
waveform, the AN noise and the IRS parameters are designed to optimize the
communication secrecy rate while meeting radar signal-to-noise ratio (SNR)
constraints. The contribution of the paper is a novel, low complexity approach
to solve the underlying optimization problem and obtain the design parameters.
In particular, we consider an alternating optimization approach, where in each
iteration, the problem is decomposed into two sub-problems, namely, one that
designs the IRS parameters, and another that jointly designs the radar waveform
and the AN. The challenges in those sub-problems are the fractional objective,
the SNR being a quartic function of the IRS parameters, and the unit-modulus
constraint on the IRS parameters. A fractional programming technique is used to
transform the fractional form objective into a more tractable non-fractional
polynomial form. A closed-form based approach is proposed for the IRS design
problem, which results in low complexity IRS design. Numerical results are
provided to demonstrate the convergence properties of the proposed system
design method, the secrecy rate and beamforming performance of the designed
system.
