  This paper proposes an architecture that integrates neural networks (NNs) and
hardware security modules using a single resistive random access memory (RRAM)
crossbar. The proposed architecture enables using a single crossbar to
implement NN, true random number generator (TRNG), and physical unclonable
function (PUF) applications while exploiting the multi-state storage
characteristic of the RRAM crossbar for the vector-matrix multiplication
operation required for the implementation of NN. The TRNG is implemented by
utilizing the crossbar's variation in device switching thresholds to generate
random bits. The PUF is implemented using the same crossbar initialized as an
entropy source for the TRNG. Additionally, the weights locking concept is
introduced to enhance the security of NNs by preventing unauthorized access to
the NN weights. The proposed architecture provides flexibility to configure the
RRAM device in multiple modes to suit different applications. It shows promise
in achieving a more efficient and compact design for the hardware
implementation of NNs and security primitives.
