2 papers
cs.CR2026
GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?
Kaixiang Zhao, Bolin Shen, Yuyang Dai +2
Graph neural networks (GNNs) deployed as cloud services can be stolen through model-extraction attacks, which train a surrogate from query responses to reproduce the target's behav…
cs.LG2026
CITED: A Decision Boundary-Aware Signature for GNNs Towards Model Extraction Defense
Bolin Shen, Md Shamim Seraj, Zhan Cheng +2
Graph neural networks (GNNs) have demonstrated superior performance in various applications, such as recommendation systems and financial risk management. However, deploying large-…