Detecting dataset poisoning attacks independent of a learning algorithm

摘要

Methods an systems to classify a training dataset of network data as a poisoned training dataset based on a first dataset-level classifier, identify and remove poison samples of the poisoned training dataset based on a sample-level classifier to produce a non-poisoned dataset, training a machine-based model to analyze network traffic based on the modified non-poisoned dataset, and analyze network traffic with the machine-based model.