OCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection

arXiv:2312.01585v2 Announce Type: replace
Abstract: Deep neural networks (DNNs) have been found vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications. There are various approaches to detect backdoor attacks, however they all make certain assumptions about the target attack to be detected and require equal and huge numbers of clean and backdoor samples for training, which renders these detection methods quite limiting in real-world circumstances.
This study proposes a novel one-class classification framework called One-class Graph …

abstract applications arxiv assumptions attacks backdoor class classification concerns cs.ai cs.cr cs.lg deployment detection dnn embedding found graph however mission networks neural networks security security concerns type vulnerable