5 papers
CLOOPD: Closing the Learner Loop in On-Policy Distillation
Keye Zheng, Hanyu Li, Zhan Cheng +1
On-policy distillation (OPD) pays twice for each fresh batch: the student generates trajectories and a stronger teacher scores them. Existing methods improve which trajectories are…
CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
Bolin Shen, Zhan Cheng, Neil Zhenqiang Gong +2
Machine Learning as a Service (MLaaS) has emerged as a widely adopted paradigm for providing access to deep neural network (DNN) models, enabling users to conveniently leverage the…
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-…
FAST-CAD: A Fairness-Aware Framework for Non-Contact Stroke Diagnosis
Tommy Sha, Zhan Cheng, Haotian Zhai +9
Stroke is an acute cerebrovascular disease, and timely diagnosis significantly improves patient survival. However, existing automated diagnosis methods suffer from fairness issues…
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks
Zhan Cheng, Bolin Shen, Tianming Sha +3
Graph Neural Networks (GNNs) have gained traction in Graph-based Machine Learning as a Service (GMLaaS) platforms, yet they remain vulnerable to graph-based model extraction attack…