GNNFormer: capturing local interactions and long-term global dependencies for APT detection in provenance graphs

GNNFormer is presented, an end-to-end framework for APT detection that leverages provenance graph representation learning and dynamically prioritizes critical nodes and interactions, enhancing its focus on high-risk patterns while filtering out irrelevant information.