Universal adversarial attacks on graph neural networks

• 主要作者: Liao, Chang
• 其他作者: Tay, Wee Peng
• 格式: Final Year Project
• 語言: English
• 出版: Nanyang Technological University 2021
• 主題: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Engineering::Electrical and electronic engineering
• 在線閱讀: https://hdl.handle.net/10356/149401
• 機構: Nanyang Technological University

This project aims to study the robustness of graph-level graph neural networks (GNNs) against universal adversarial attacks in white-box and grey-box scenarios. Graph-level GNNs are widely used in critical domains such as quantum chemistry, drug discovery, while the robustness of them against un...