Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency

arXiv:2403.10717v1 Announce Type: new
Abstract: Modern machine learning (ML) systems demand substantial training data, often resorting to external sources. Nevertheless, this practice renders them vulnerable to backdoor poisoning attacks. Prior backdoor defense strategies have primarily focused on the identification of backdoored models or poisoned data characteristics, typically operating under the assumption of access to clean data. In this work, we delve into a relatively underexplored challenge: the automatic identification of backdoor data within a poisoned dataset, all under realistic conditions, …

arxiv backdoor cs.ai cs.cr cs.lg data prediction type