 As deep learning moves from the lab into the world, research and experience shows that artificial neural networks are vulnerable to hacks and deception.By identifying patterns that these systems use to function, attackers can modify inputs to ANNs in such a way that the ANN finds a match that human observers would not recognize.For example, an attacker can make subtle changes to an image such that the ANN finds a match even though the image looks to a human nothing like the search target.