Publications

  • Ruyi Ding*, Tianhong Xu*, Aidong Adam Ding, Yunsi Fei. Graph in the Vault: Protecting Edge GNN Inference with Trusted Execution Environment. Design Automation Conference. (DAC2025)PDF
  • Ruyi Ding, Cheng Gongye, Davis Ranney, Aidong Adam Ding, Yunsi Fei. MACPruning: Dynamic Operation Pruning to Mitigate Side-Channel DNN Model Extraction. IEEE International Symposium on Hardware Oriented Security and Trust (HOST 2025) Best Paper Awards Nomination PDF
  • Ruyi Ding, Tong Zhou, Lili Su, Aidong Adam Ding, Xiaolin Xu, Yunsi Fei, Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing. (NDSS Symposium 2025, accepted with minor revision). GitHub PDF
  • Shijin Duan*, Ruyi Ding*, Jiaxing He, Aidong Adam Ding, Yunsi Fei, Xiaolin Xu, GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction. The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024). PDF
  • Ruyi Ding, Lili Su, Aidong Adam Ding, Yunsi Fei, Non-transferable Pruning. The 18th European Conference on Computer Vision (ECCV 2024). GitHub PDF
  • Ruyi Ding*, Shijin Duan*, Xiaolin Xu, Yunsi Fei, VertexSerum: Poisoning Graph Neural Networks for Link Inference. International Conference on Computer Vision (ICCV 2023). GitHub PDF
  • Ruyi Ding, Cheng Gongye, Siyue Wang, Aidong Adam Ding, Yunsi Fei, EMShepherd: Detecting Adversarial Samples via Side-channel Leakage. ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2023). Distinguished Paper Award. GitHub PDF
  • Ruyi Ding, Ziyue Zhang, Xiang Zhang, Cheng Gongye, Yunsi Fei, & Aidong Adam Ding A cross-platform cache timing attack framework via deep learning. In 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE 2022). Best Paper Awards Nomination. GitHub PDF
  • Yize Li, Pu Zhao, Ruyi Ding, Tong Zhou, Yunsi Fei, Xiaolin Xu, Xue Lin Neural Architecture Search for Adversarial Robustness via Learnable Pruning. Frontiers in High Performance Computing.
  • Xiang Zhang, Ziyue Zhang, Ruyi Ding, Cheng Gongye, Aidong Adam Ding, & Yunsi Fei, (2022, June). Ran$Net: An Anti-Ransomware Methodology based on Cache Monitoring and Deep Learning. In Proceedings of the Great Lakes Symposium on VLSI (GLSVLSI 2022).
  • Shixiang Zhu, Ruyi Ding, Minghe Zhang, Pascal Van Hentenryck, & Yao Xie, Spatio-temporal point processes with attention for traffic congestion event modeling. IEEE Transactions on Intelligent Transportation Systems. (2021)
  • Shixiang Zhu, Minghe Zhang, Ruyi Ding, & Yao Xie, Deep Fourier Kernel for Self-Attentive Point Processes. In International Conference on Artificial Intelligence and Statistics (AISTATS 2021).
  • Fan Zhang, Xiaoxuan Lou, Xinjie Zhao, Shivam Bhasin, Wei He, Ruyi Ding, Samiya Qureshi, Kui Ren. Persistent fault analysis on block ciphers. IACR Transactions on Cryptographic Hardware and Embedded Systems. (2018)