  This work presents a web-based interactive neural network (NN) calculator and
a NN inefficiency measurement that has been investigated for the purpose of
detecting trojans embedded in NN models. This NN Calculator is designed on top
of TensorFlow Playground with in-memory storage of data and NN graphs plus
coefficients. It is "like a scientific calculator" with analytical,
visualization, and output operations performed on training datasets and NN
architectures. The prototype is aaccessible at
https://pages.nist.gov/nn-calculator. The analytical capabilities include a
novel measurement of NN inefficiency using modified Kullback-Liebler (KL)
divergence applied to histograms of NN model states, as well as a
quantification of the sensitivity to variables related to data and NNs. Both NN
Calculator and KL divergence are used to devise a trojan detector approach for
a variety of trojan embeddings. Experimental results document desirable
properties of the KL divergence measurement with respect to NN architectures
and dataset perturbations, as well as inferences about embedded trojans.
