Exploiting artificial neural networks machine learning errors for attacks on AI systems

The paper provides an overview of methods and approaches to attacks on neural network-based artificial intelligence systems. It is shown that since 2015, global researchers have been intensively developing methods and approaches for attacks on artificial neural networks, while the existing ones may have critical consequences for artificial intelligence systems operations. We come to the conclusion that theory and methodology for artificial neural networks is to be elaborated, since trusted artificial intelligence systems cannot be created in the framework of the current paradigm.