How understanding the training process of deep neural networks help in interpreting results and non-robustness manifested in simple adversarial attacks?

I think this is a necessary research direction for the reliable and widespread use of deep neural networks for critical applications. What are the current approaches to understand the optimization process inherent in the training of such networks?