Influencer Backdoor Attack on Semantic Segmentation

arXiv:2303.12054v3 Announce Type: replace
Abstract: When a small number of poisoned samples are injected into the training dataset of a deep neural network, the network can be induced to exhibit malicious behavior during inferences, which poses potential threats to real-world applications. While they have been intensively studied in classification, backdoor attacks on semantic segmentation have been largely overlooked. Unlike classification, semantic segmentation aims to classify every pixel within a given image. In this work, we explore backdoor attacks on segmentation …

abstract applications arxiv attacks backdoor behavior classification cs.cv dataset deep neural network inferences influencer network neural network samples segmentation semantic small threats training type world