  In this paper, we propose an iterative scheme for distributed
Byzantineresilient estimation of a gradient associated with a black-box model.
Our algorithm is based on simultaneous perturbation, secure state estimation
and two-timescale stochastic approximations. We also show the performance of
our algorithm through numerical experiments.
