1. A method, comprising: generating, by a device in a network, an expected traffic model, wherein a training set of data used to train a machine learning attack detector is also used to generate the expected traffic model, and the expected traffic model represents an overall set of behaviors for which the machine learning attack detector has already been trained; transmitting, by the device, the expected traffic model to one or more nodes in the network, the expected traffic model used by the one or more nodes to identify an observed traffic behavior that was not present in the training set of data used to train machine learning attack detector, wherein the expected traffic model triggers the machine learning attack detector to analyze the observed traffic behavior when the observed traffic behavior is expected, and wherein the expected traffic model triggers the one or more nodes to prevent the machine learning attack detector from analyzing the observed traffic behavior when the observed traffic behavior is unexpected; receiving, at the device, an unexpected behavior notification from a particular node of the one or more nodes, wherein the particular node generates the unexpected behavior notification based on a comparison between the expected traffic model and an observed traffic behavior at the particular node that results in the observed traffic behavior being unexpected by the expected traffic model; and updating, by the device, the machine learning attack detector to account for the observed traffic behavior.