  The potential of Reconfigurable Intelligent Surfaces (RISs) for
energy-efficient and performance-boosted wireless communications is recently
gaining remarkable research attention, motivating their consideration for
various $5$-th Generation (5G) Advanced and beyond applications. In this paper,
we consider a Multiple-Input Multiple-Output (MIMO) Physical Layer Security
(PLS) system with multiple data streams including one legitimate passive RIS
and one malicious passive RIS, with the former being transparent to the
multi-antenna eavesdropper and the latter's presence being unknown at the
legitimate multi-antenna transceivers. We first present a novel threat model
for the RIS-boosted eavesdropping system and design a joint optimization
framework for the eavesdropper's receive combining matrix and the reflection
coefficients of the malicious RIS. Focusing next on the secrecy rate
maximization problem, we present an RIS-empowered PLS scheme that jointly
designs the legitimate precoding matrix and number of data streams, the
Artificial Noise (AN) covariance matrix, the receive combining matrix, and the
reflection coefficients of the legitimate RIS. The proposed optimization
algorithms, whose convergence to at least local optimum points is proved, are
based on alternating maximization, minorization-maximization, and manifold
optimization, including semi-closed form expressions for the optimization
variables. Our extensive simulation results for two representative system
setups reveal that, in the absence of a legitimate RIS, transceiver spatial
filtering and AN are incapable of offering non-zero secrecy rates, even for
malicious RISs with small numbers of elements. However, when an $L$-element
legitimate RIS is deployed, confidential communication can be safeguarded
against eavesdropping systems possessing even more than a $5L$-element
malicious RIS.
