  User privacy protection is considered a critical issue in wireless networks,
which drives the demand for various secure information interaction techniques.
In this paper, we introduce an intelligent reflecting surface (IRS)-aided
security classification wireless communication system, which reduces the
transmit power of the base station (BS) by classifying users with different
security requirements. Specifically, we divide the users into confidential
subscribers with secure communication requirements and general communication
users with simple communication requirements. During the communication period,
we guarantee the secure rate of the confidential subscribers while ensuring the
service quality of the general communication users, thereby reducing the
transmit power of the BS. To realize such a secure and green information
transmission, the BS implements a beamforming design on the transmitted signal
superimposed with artificial noise (AN) and then broadcasts it to users with
the assistance of the IRS's reflection. We develop an alternating optimization
framework to minimize the BS downlink power with respect to the active
beamformers of the BS, the AN vector at the BS, and the reflection phase shifts
of the IRS. A successive convex approximation (SCA) method is proposed so that
the nonconvex beamforming problems can be converted to tractable convex forms.
The simulation results demonstrate that the proposed algorithm is convergent
and can reduce the transmit power by 20\% compared to the best benchmark
scheme.
