Welcome to Yuanyuan’ homepage!

I’m currently a final year Ph.D. student at CSE department, HKUST. I’m very fortunate and honored to work under the supervision of Prof. Shuai Wang. During my Ph.D. study, I also spent a wonderful year at ETH Zurich, supervised by Prof. Zhendong Su. Before joining HKUST, I received my B.S. from Fudan University.

My research aims to comprehensively harden and secure modern AI systems. I pursue this goal from the algorithm (e.g., new attacks), software (e.g., testing, verification), and hardware (e.g., side channel, low-level executable) perspectives.

E-mail: yyuanaq [at] cse.ust.hk

Education & Experience

• Ph.D. in Computer Science and Engineering. The Hong Kong University of Science and Technology. Sep. 2020 - present.
• Visiting Researcher. AST lab, ETH Zurich. Sep. 2022 - Sep. 2023.
• B.S. in Computer Science. Fudan University. Sep. 2016 - July 2020.

Selected Publications

• [NDSS] MPCDiff: Testing and Repairing MPC-Hardened Deep Learning Models.
  Qi Pang, Yuanyuan Yuan, and Shuai Wang.
  In 31st Network and Distributed System Security Symposium, 2024.

• [NeurIPS] Explain Any Concept: Segment Anything Meets Concept-Based Explanation.
  Ao Sun, Pingchuan Ma, Yuanyuan Yuan, and Shuai Wang.
  In 37th Conference on Neural Information Processing Systems, 2023.
  [preprint]

• [Black Hat USA] BTD: Unleashing the Power of Decompilation for x86 Deep Neural Network Executables.
  Zhibo Liu, Yuanyuan Yuan, Xiaofei Xie, Tianxiang Li, Wenqiang Li, and Shuai Wang.
  In 26th Black Hat USA, 2023.

• [IEEE S&P] ADI: Adversarial Dominating Inputs in Vertical Federated Learning Systems.
  Qi Pang, Yuanyuan Yuan, Shuai Wang, and Wenting Zheng.
  In 44th IEEE Symposium on Security and Privacy, 2023.
  [extended version]

• [NDSS] OBSan: An Out-Of-Bound Sanitizer to Harden DNN Executables.
  Yanzuo Chen, Yuanyuan Yuan$^\dagger$, and Shuai Wang$^\dagger$.
  In 30th Network and Distributed System Security Symposium, 2023.
  $^\dagger$ Corresponding author.
  [project page], [code]

• [USENIX Security] Precise and Generalized Robustness Certification for Neural Networks.
  Yuanyuan Yuan, Shuai Wang, and Zhendong Su.
  In 32nd USENIX Security Symposium, 2023.
  [preprint], [code]

• [USENIX Security] CacheQL: Quantifying and Localizing Cache Side-Channel Vulnerabilities in Production Software.
  Yuanyuan Yuan, Zhibo Liu, and Shuai Wang.
  In 32nd USENIX Security Symposium, 2023.
  [extended version], [findings], [code]

• [USENIX Security] Decompiling x86 Deep Neural Network Executables.
  Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, and Lei Ma.
  In 32nd USENIX Security Symposium, 2023.
  🌟 Artifact Evaluation Badges: Available; Functional; Reproduced.
  [extended version], [code]

• [ICSE] CC: Causality-Aware Coverage Criterion for Deep Neural Networks.
  Zhenlan Ji, Pingchuan Ma$^\dagger$, Yuanyuan Yuan$^\dagger$, and Shuai Wang.
  In 45th IEEE/ACM International Conference on Software Engineering, 2023.
  $^\dagger$ Corresponding author.
  [code]

• [ICSE] Revisiting Neuron Coverage for DNN Testing: A Layer-Wise and Distribution-Aware Criterion.
  Yuanyuan Yuan, Qi Pang, and Shuai Wang.
  In 45th IEEE/ACM International Conference on Software Engineering, 2023.
  [extended version], [code]

• [ASE] Unveiling Hidden DNN Defects with Decision-Based Metamorphic Testing.
  Yuanyuan Yuan, Qi Pang, and Shuai Wang.
  In 37th IEEE/ACM International Conference on Automated Software Engineering, 2022.
  [extended version], [code]

• [ISSTA] MDPFuzz: Testing Models Solving Markov Decision Processes.
  Qi Pang, Yuanyuan Yuan, and Shuai Wang.
  In 31st International Symposium on Software Testing and Analysis, 2022.
  [code]

• [TIFS] NeuralD: Detecting Indistinguishability Violations of Oblivious RAM with Neural Distinguishers.
  Pingchuan Ma, Zhibo Liu, Yuanyuan Yuan, and Shuai Wang.
  In IEEE Transactions on Information Forensics and Security, 2022.
  [code]

• [TSE] Enhancing DNN-Based Binary Code Function Search With Low-Cost Equivalence Checking.
  Huaijin Wang, Pingchuan Ma, Yuanyuan Yuan, Zhibo Liu, Shuai Wang, Qiyi Tang, Sen Nie, and Shi Wu.
  In IEEE Transactions on Software Engineering, 2022.
  [code]

• [SIGMETRICS] Metamorphic Testing of Deep Learning Compilers.
  Dongwei Xiao, Zhibo Liu, Yuanyuan Yuan, Qi Pang, and Shuai Wang.
  In ACM Sigmetrics/Performance, 2022.
  [code]

• [USENIX Security] Automated Side Channel Analysis of Media Software with Manifold Learning.
  Yuanyuan Yuan, Qi Pang, and Shuai Wang.
  In 31st USENIX Security Symposium, 2022.
  🌟 Artifact Evaluation Badges: Available; Functional; Reproduced.
  [extended version], [code]

• [IEEE S&P] SoK: Demystifying Binary Lifters Through the Lens of Downstream Applications.
  Zhibo Liu, Yuanyuan Yuan, Shuai Wang, and Yuyan Bao.
  In 43rd IEEE Symposium on Security and Privacy, 2022.
  [code]

• [CVPR] Perception Matters: Detecting Perception Failures of VQA Models Using Metamorphic Testing.
  Yuanyuan Yuan, Shuai Wang, Mingyue Jiang, and Tsong Yueh Chen.
  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021.
  [code]

• [ICLR] Private Image Reconstruction from System Side Channels Using Generative Models.
  Yuanyuan Yuan, Shuai Wang, and Junping Zhang.
  In International Conference on Learning Representations, 2021.
  [code]

Academic Services

• Program Committee: USENIX Security 2023 (Artifact Evaluation), OSDI 2022 and USENIX ATC 2022 (Artifact Evaluation), ISSTA 2022 (Artifact Evaluation).

• Reviewer/Sub-/Co-reviewer: USENIX Security 2023, ISSTA 2023, FSE 2023, ASE 2022, CCS 2022.

Teaching Experience

• Teaching Assistant: COMP3632: Principles of Cybersecurity. HKUST, Fall 2021.
• Teaching Assistant: COMP3632: Principles of Cybersecurity. HKUST, Spring 2021.
• Teaching Assistant: Introduction to Computer System. Fudan University, Fall 2018.

Updated on 22 Sep. 2023