Abstract:The label flipping attack is a special poisoning attack in the adversarial environment. By adding noise to the data, it destroys the learning process of the model and affects the decision-making performance of the model. Recent literature work uses semi-supervised learning techniques to defend against label flipping attacks. However, these methods require a clean dataset to achieve their goals. This study proposes a novel label noise processing framework to correct the labels of contaminated samples in the dat… Show more
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.