shuai Shuai Wang

Associate Professor
Department of Computer Science and Engineering
Hong Kong University of Science and Technology

Office: CYT 3003

E-mail: shuaiw at cse.ust.hk

I am an associate professor with substantiation (tenure) at CSE, HKUST. Prior to that, I was an assistant professor at CSE, HKUST (2019-2024), and was a postdoctoral scholar in the AST lab at ETH Zurich (2018-2019). I received the Ph.D. degree from Penn State University, and the B.S. degree from Peking University.

My research covers Computer Security and Privacy as well as Software Engineering. I study important attributes (security, privacy, satefy, ethics, fairness, etc.) in software, artificial intelligence, systems, and more importantly, their integrations, e.g., exploiting/hardening AI models from system perspectives, studying AI ethics with software testing/verification, supporting privacy computing via software and system infrastructures, and using LLMs for software fuzzing.

I am the recipient of a Google Research Scholar Award (2023), two CCF-Tencent Rhino-Bird Young Faculty Open Research Awards (2022 and 2020), and a HK-UGC Early Career Award (2020).

Teaching

  • CSIT5730: Principles of Cybersecurity (Fall 2024)
  • COMP2011: Programming with C++ (Fall 2024)
  • COMP3632: Principles of Cybersecurity (Spring 2024)
  • COMP3632: Principles of Cybersecurity (Fall 2023)
  • COMP3632: Principles of Cybersecurity (Spring 2023)
  • COMP4971A: Independent Work on Systems Security (Spring 2023)
  • COMP4971B: Independent Work on Systems Security (Spring 2023)
  • COMP3632: Principles of Cybersecurity (Fall 2022)
  • COMP3632: Principles of Cybersecurity (Spring 2022)
  • COMP3632: Principles of Cybersecurity (Fall 2021)
  • COMP3632: Principles of Cybersecurity (Spring 2021)
  • COMP6613C: Topics in Computer Security and Privacy (Spring 2021)
  • COMP3632: Principles of Cybersecurity (Fall 2020)
  • COMP3632: Principles of Cybersecurity (Fall 2019)
  • COMP4971A: Independent Work on Software Fuzz Testing (Fall 2019)

Current Team Members

Postdoc

Ph.D. Students

RA/Intern/UG

  • Zimo Ji (2024 Summer). Co-advised with Prof. Daoyuan Wu
  • Yufan Chen (2024 Summer). Co-advised with Prof. Daoyuan Wu
  • Kaiwen Yang (2024 RA) Co-advised with Prof. Daoyuan Wu
  • LAU Pak Hin (2024 Co-OP)

Former Students

  • Pingchuan Ma (Ph.D.#4) 2020-2024. Thesis: Algorithms, Applications, and Verification of Causal Structure Learning.
  • Yuanyuan Yuan (Ph.D.#3) 2020-2024. Thesis: Side Channel Analysis for AI Infrastructures.
  • Sen Li (MPhil @ CSE HKUST) 2022-2024. Co-advised with Prof. Minhao Cheng. Thesis: Towards Trustworthy Visual Generative Models: Reliable and Controllable Generation of Diffusion Models.
  • Yichen Li (MPhil @ CSE HKUST) 2022-2024. Thesis: Testing Secure Multi-Party Computation Compilers. Ph.D. student @ SusTech
  • Huaijin Wang (Ph.D.#2) 2019-2023. Thesis: Advanced Binary Similarity Analysis and Its Downstream Applications.
  • Zhibo Liu (Ph.D.#1) 2019-2023. Thesis: Towards Assessing and Enhancing Modern Software Reverse Engineering. CSE Best PhD Dissertation Award - Honorable Mention.
  • Yuzhou Fang (UG@Sichuan University) 2022-2023. Co-advised with Prof. Daoyuan Wu. Smart Contract Security. Ph.D. student @ USC
  • Zhaoyu Wang (UG@Tongji University) 2022-2023. Co-advised with Pingchuan Ma. Thesis: Program Analysis. Ph.D. student @ HKUST
  • Ao Sun (UG@UIUC) 2023. Co-advised with Pingchuan Ma. Research on LLM Security. Ph.D. student @ HKUST
  • Yiteng Peng (UG@USTC) 2023. Co-advised with Yuanyuan Yuan. Membership Inference Attack. Ph.D. student @ HKUST
  • SINGHAL, Sarthak (2023 Spring UG@HKUST). COMP 4971 (Independent Work) on Intrusion Detection. Security Intern @ Deloitte
  • Qi Wu (UG@HKUST). 2022-2023. Thesis: NFT Security: Rug Pull Detection. MS student @ CMU.
  • Wenbo Li (UG@HKUST). 2022-2023. MS student @ USC.
  • Qihao He (UG@HKUST). 2022-2023. MS student @ TAMU.
  • Qi Pang (MPhil @ CSE HKUST). 2020-2022. Thesis: Testing Models Solving Markov Decision Processes. Ph.D. student @ CMU.
  • Wai Kin WONG (MPhil @ CSE HKUST). 2019-2021. Thesis on software security. Ph.D. student @ HKUST.
  • Kun Hung LUNG (MPhil @ CSE HKUST). Thesis on systems security. 2019-2021. Engineer @ a start-up cybersecurity company.
  • Wei Chen (MPhil @ CSE HKUST). 2019-2021. Thesis on systems security. RA @ HKUST.
  • Wangkai Jin (UG @ CSE UNottingham Ningbo). 2021 Summer intern on AI privacy projects. MSCS student @ Duke University.
  • Yujie Wang (UG @ CSE HKUST). 2020-2021 Thesis: Privacy-Preserving Security Analysis. Ph.D. student @ Washington University in St. Louis.
  • Xirui Nie (UG @ Fudan University). 2020 Summer intern on compiler & OS security projects. Ph.D. student @ CUHK.
  • Reiff Loris (UG @ ETH Zurich, co-advised with Prof. Zhendong Su). Thesis: Context-Aware Obfuscation: A Step Towards Defeating Adversary Symbolic Analysis. Continued Masters study @ ETH Zurich.
  • Nguyen Andy (UG @ ETH Zurich, co-advised with Prof. Zhendong Su). Thesis: Detecting Vulnerabilities in Real-World Software with Fuzz Testing. Information Security Engineer @ Google.

Organization

Program committees

  • 2025: IEEE S&P, USENIX Security
  • 2024: IEEE S&P, USENIX Security, FSE, ISSTA
  • 2023: IEEE S&P, USENIX Security, CCS, FSE, ISSTA, ASE, PoPETs/PETS, PRDC
  • 2022: CCS, ASE, ICSE (SEET), AsiaCCS, NDSS (BAR), DBTest
  • 2021: ICSE (AE), AsiaCCS

Selected Publications

  • Preserving Privacy in Software Composition Analysis: A Study of Technical Solutions and Enhancements.
    Huaijin Wang, Zhibo Liu, Yanbo Dai, Shuai Wang, Qiyi Tang, Sen Nie, and Shi Wu. ICSE 2025
  • Testing and Understanding Deviation Behaviors in FHE-hardened Machine Learning Models.
    Yiteng Peng, Daoyuan Wu, Zhibo Liu, Dongwei Xiao, Zhenlan Ji, Juergen Rahmel, and Shuai Wang. ICSE 2025
  • BitShield: Defending Against Bit-Flip Attacks on DNN Executables.
    Yanzuo Chen, Zhibo Liu, Yuanyuan Yuan, Sihang Hu, Tianxiang Li, and Shuai Wang. NDSS 2025
  • CipherSteal: Stealing Input Data from TEE-Shielded Neural Networks with Ciphertext Side Channels.
    Yuanyuan Yuan, Zhibo Liu, Sen Deng, Yanzuo Chen, Shuai Wang, Yinqian Zhang, and Zhendong Su. IEEE Security & Privacy 2025
  • MTZK: Testing and Exploring Bugs in Zero-Knowledge (ZK) Compilers.
    Dongwei Xiao, Zhibo Liu, Yiteng Peng, and Shuai Wang. NDSS 2025
  • Compiled Models, Built-In Exploits: Uncovering Pervasive Bit-Flip Attack Surfaces in DNN Executables.
    Yanzuo Chen, Zhibo Liu, Yuanyuan Yuan, Sihang Hu, Tianxiang Li, and Shuai Wang. NDSS 2025
  • Your Fix Is My Exploit: Enabling Comprehensive DL Library API Fuzzing with Large Language Models.
    Kunpeng Zhang, Shuai Wang, Jitao Han, Xiaogang Zhu, Xian Li, Shaohua Wang, and Sheng Wen. ICSE 2025
  • The Devil is in the (Micro-) Architectures: Uncovering New Side-Channel and Bit-Flip Attack Surfaces in DNN Executables.
    Yanzuo Chen, Zhibo Liu, Yuanyuan Yuan, Sihang Hu, Tianxiang Li, and Shuai Wang. Black Hat Europe 2024
  • Split and Merge: Aligning Position Biases in LLM-based Evaluators.
    Zongjie Li, Chaozheng Wang, Pingchuan Ma, Daoyuan Wu, Shuai Wang, Cuiyun Gao, and Yang Liu. EMNLP 2024 (main)
  • DeepCache: Revisiting Cache Side-Channel Attacks in Deep Neural Networks Executables.
    Zhibo Liu, Yuanyuan Yuan, Yanzuo Chen, Sihang Hu, Tianxiang Li, and Shuai Wang. CCS 2024
  • HyperTheft: Thieving Model Weights from TEE-Shielded Neural Networks via Ciphertext Side Channels.
    Yuanyuan Yuan, Zhibo Liu, Sen Deng, Yanzuo Chen, Shuai Wang, Yinqian Zhang, and Zhendong Su. CCS 2024
  • MOAT: Towards Safe BPF Kernel Extension.
    Hongyi Lu, Shuai Wang, Yechang Wu, Wanning He, and Fengwei Zhang. USENIX Security 2024
  • See the Forest, not Trees: Unveiling and Escaping the Pitfalls of Error-Triggering Inputs in Neural Network Testing.
    Yuanyuan Yuan, Shuai Wang and Zhendong Su. ISSTA 2024
  • Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior.
    Pingchuan Ma, Rui Ding, Qiang Fu, Jiaru Zhang, Shuai Wang, Shi Han, and Dongmei Zhang. KDD 2024
  • Are We There Yet? Filling the Gap Between ML-Based Binary Similarity Analysis and Binary Software Composition Analysis.
    Huaijin Wang, Zhibo Liu, Shuai Wang, Ying Wang, Qiyi Tang, Sen Nie, and Shi Wu. IEEE EuroS&P 2024
  • LLM for Mobile: An Initial Roadmap.
    Daihang Chen, Yonghui Liu, Mingyi Zhou, Yanjie Zhao, Haoyu Wang, Shuai Wang, Xiao Chen, Tegawende Bissyande, Jacques Klein, and Li Li. 2030 Software Engineering at FSE 2024
  • Provably Valid and Diverse Mutations of Real-World Media Data for DNN Testing.
    Yuanyuan Yuan, Qi Pang, and Shuai Wang. TSE 2024
  • PP-CSA: Practical Privacy-Preserving Software Call Stack Analysis.
    Zhaoyu Wang, Pingchuan Ma, Huaijin Wang, and Shuai Wang. OOPSLA 2024
  • Metamorphic Testing of Secure Multi-Party Computation (MPC) Compilers.
    Yichen Li, Dongwei Xiao, Zhibo Liu, Qi Pang, and Shuai Wang. FSE 2024
  • DTD: Comprehensive and Scalable Testing for Debuggers.
    Hongyi Lu, Zhibo Liu, Shuai Wang, and Fengwei Zhang. FSE 2024
  • Strengthening Supply Chain Security with Fine-grained Safe Patch Identification.
    Changhua Luo, Wei Meng, and Shuai Wang. ICSE 2024
  • Testing Graph Database Systems via Graph-Aware Metamorphic Relations.
    Zeyang Zhuang, Penghui Li, Pingchuan Ma, Wei Meng, and Shuai Wang. VLDB 2024
  • Evaluating C/C++ Vulnerability Detectability of Query-Based Static Application Security Testing Tools.
    Zongjie Li, Zhibo Liu, Wai Kin Wong, Pingchuan Ma, and Shuai Wang. TDSC 2024
  • On Extracting Specialized Code Abilities from Large Language Models: A Feasibility Study.
    Zongjie Li, Chaozheng Wang, Pingchuan Ma, Chaowei Liu, Shuai Wang, Daoyuan Wu, Cuiyun Gao, Yang Liu. ICSE 2024
  • BinAug: Enhancing Binary Similarity Analysis with Low-Cost Input Repairing.
    Wai Kin Wong, Huaijin Wang, Zongjie Li, and Shuai Wang. ICSE 2024
  • Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning.
    Pingchuan Ma, Zhenlan Ji, Peisen Yao, Shuai Wang, and Kui Ren. ICSE 2024
  • MPCDiff: Testing and Repairing MPC-Hardened Deep Learning Models.
    Qi Pang, Yuanyuan Yuan, and Shuai Wang. NDSS 2024
  • InsightPilot: An LLM-Empowered Automated Data Exploration System.
    Pingchuan Ma, Rui Ding, Shuai Wang, Han Shi, and Dongmei Zhang. EMNLP 2023 (Demo Track)
  • Explain Any Concept: Segment Anything Meets Concept-Based Explanation.
    Ao Sun, Pingchuan Ma, Yuanyuan Yuan, and Shuai Wang. NeurIPS 2023
  • Protecting Intellectual Property of Large Language Model-Based Code Generation APIs via Watermarks.
    Zongjie Li, Chaozheng Wang, Shuai Wang, and Cuiyun Gao. CCS 2023
  • REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes.
    Chaozheng Wang, Li Zongjie, Yun Peng, Shuzheng Gao, Sirong Chen, Shuai Wang, Cuiyun Gao, and Michael Lyu. ASE 2023 (Industry Challenge Track) Distinguished Paper Award
  • Causality-Aided Trade-off Analysis for Machine Learning Fairness.
    Zhenlan Ji, Pingchuan Ma, Shuai Wang, and Yanhui Li. ASE 2023
  • PerfCE: Performance Debugging on Databases with Chaos Engineering-Enhanced Causality Analysis.
    Zhenlan Ji, Pingchuan Ma and Shuai Wang. ASE 2023
  • PHYFU: Fuzzing Modern Physics Simulation Engines.
    Dongwei Xiao, Zhibo Liu and Shuai Wang. ASE 2023 ACM SIGSOFT Distinguished Paper Award
  • Towards Practical Federated Causal Structure Learning.
    Zhaoyu Wang, Pingchuan Ma, and Shuai Wang. ECML-PKDD 2023
  • Precise and Generalized Robustness Certification for Neural Networks.
    Yuanyuan Yuan, Shuai Wang, and Zhendong Su. USENIX Security 2023 [paper]
  • 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. Blackhat USA 2023
  • Exploiting Code Reuse Attacks from Obfuscated Programs.
    Naiqian Zhang, Daroc Alden, Dongpeng Xu, Shuai Wang, Trent Jaeger, and Wheeler Ruml. DSN 2023
  • Beyond "Protected" and "Private": An Empirical Security Analysis of Custom Function Modifiers in Smart Contracts.
    Yuzhou Fang, Daoyuan Wu, Xiao Yi, Shuai Wang, Yufan Chen, Mengjie Chen, Yang Liu, and Lingxiao Jiang. ISSTA 2023
  • Secure Federated Correlation Test and Entropy Estimation.
    Qi Pang, Lun Wang, Shuai Wang, Wenting Zheng, and Dawn Song. ICML 2023
  • ADI: Adversarial Dominating Inputs in Vertical Federated Learning Systems.
    Qi Pang, Yuanyuan Yuan, Shuai Wang, and Wenting Zheng. IEEE Security & Privacy 2023 [paper]
  • XInsight: eXplainable Data Analysis Through The Lens of Causality.
    Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, and Dongmei Zhang. SIGMOD 2023[paper]
  • Byzantine-Robust Federated Learning with Optimal Statistical Rates.
    Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, and Michael Jordan. AISTATS 2023 [paper]
  • Exploring Missed Optimizations in WebAssembly Optimizers.
    Zhibo Liu, Dongwei Xiao, Zongjie Li, Shuai Wang, and Wei Meng. ISSTA 2023
  • OBSan: An Out-Of-Bound Sanitizer to Harden DNN Executables.
    Yanzuo Chen, Yuanyuan Yuan, and Shuai Wang. NDSS 2023 [paper]
  • Revisiting Neuron Coverage for DNN Testing: A Layer-Wise and Distribution-Aware Criterion.
    Yuanyuan Yuan, Qi Pang, and Shuai Wang. ICSE 2023 [paper]
  • Metamorphic Shader Fusion for Testing Graphics Shader Compilers.
    Dongwei Xiao, Zhibo Liu, and Shuai Wang. ICSE 2023 [paper]
  • CC: Causality-Aware Coverage Criterion for Deep Neural Networks.
    Zhenlan Ji, Pingchuan Ma, Yuanyuan Yuan, and Shuai Wang. ICSE 2023 [paper]
  • CCTEST: Testing and Repairing Code Completion Systems.
    Zongjie Li, Chaozheng Wang, Zhibo Liu, Haoxuan Wang, Dong Chen, Shuai Wang, and Cuiyun Gao. ICSE 2023 [paper]
  • CacheQL: Quantifying and Localizing Cache Side-Channel Vulnerabilities in Production Software.
    Yuanyuan Yuan, Zhibo Liu, and Shuai Wang. USENIX Security 2023 [paper]
  • CipherH: Automated Detection of Ciphertext Side-channel Vulnerabilities in Cryptographic Implementations.
    Sen Deng, Mengyuan Li, Yining Tang, Shuai Wang, Shoumeng Yan, and Yinqian Zhang. USENIX Security 2023 [paper]
  • Decompiling x86 Deep Neural Network Executables.
    Zhibo Liu, Yuanyuan Yuan, Shuai Wang, Xiaofei Xie, and Lei Ma. USENIX Security 2023 [paper]
  • sem2vec: Semantics-Aware Assembly Tracelet Embedding.
    Huaijin Wang, Pingchuan Ma, Shuai Wang, Qiyi Tang, Sen Nie, and Shi Wu. ACM TOSEM 2022 [paper]
  • Unveiling the Hidden Defection of DNN Testing with Decision-Based Metamorphic Oracle.
    Yuanyuan Yuan, Qi Pang, and Shuai Wang. ASE 2022 [paper]
  • Cache Refinement Type for Side-channel Detection of Cryptographic Software.
    Ke Jiang, Yuyan Bao, Shuai Wang, Zhibo Liu, and Tianwei Zhang. CCS 2022 [paper]
  • Deceiving Deep Neural Networks-Based Binary Code Matching with Adversarial Programs.
    Wai Kin Wong, Huaijin Wang, Pingchuan Ma, Shuai Wang, Mingyue Jiang, Tsong Yueh Chen, Qiyi Tang, Sen Nie, and Shi Wu. ICSME 2022[paper]
  • NOLEAKS: Differentially Private Causal Discovery Under Functional Causal Model.
    Pingchuan Ma, Zhenlan Ji, Qi Pang, and Shuai Wang. IEEE TIFS 2022 [paper]
  • On the Effectiveness of Testing Sentiment Analysis Systems with Metamorphic Testing.
    Mingyue Jiang, Shuai Wang, and Tsong Yueh Chen. Elsevier IST 2022 [paper]
  • ML4S: Learning Causal Skeleton from Vicinal Graphs.
    Pingchuan Ma, Rui Ding, Haoyue Dai, Yuanyuan Jiang, Shuai Wang, Shi Han, and Dongmei Zhang. KDD 2022 [paper]
  • Unlearnable Examples: Protecting Open-Source Software from Unauthorized Neural Code Learning.
    Zhenlan Ji, Pingchuan Ma, and Shuai Wang. SEKE 2022 [paper]
  • MDPFuzz: Testing Models Solving Markov Decision Processes.
    Qi Pang, Yuanyuan Yuan, and Shuai Wang. ISSTA 2022 [paper]
  • TORPEDO: A Fuzzing Framework for Discovering Adversarial Container Workloads.
    Kent McDonough, Xing Gao, Shuai Wang, and Haining Wang. DSN 2022
  • NeuralD: Detecting Indistinguishability Violations of Oblivious RAM with Neural Distinguishers.
    Pingchuan Ma, Zhibo Liu, Yuanyuan Yuan, and Shuai Wang. IEEE TIFS 2022 [paper]
  • 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. IEEE TSE 2022 [paper]
  • FED-X2: Privacy Preserving Federated Correlation Test.
    Lun Wang*, Qi Pang*, Shuai Wang, Dawn Song. PPAI-22 co-located with AAAI 2022
  • Metamorphic Testing of Deep Learning Compilers.
    Dongwei Xiao, Zhibo Liu, Yuanyuan Yuan, Qi Pang, and Shuai Wang. SIGMETRICS 2022 [paper]
  • Unleashing the Power of Compiler Intermediate Representation to Enhance Neural Program Embeddings.
    Zongjie Li, Pingchuan Ma, Huaijin Wang, Shuai Wang, Qiyi Tang, Sen Nie, and Shi Wu. ICSE 2022 [paper]
  • MT-Teql: Evaluating and Augmenting Neural NLIDB on Real-world Linguistic and Schema Variations.
    Pingchuan Ma and Shuai Wang. VLDB 2022 [paper]
  • Automated Side Channel Analysis of Media Software with Manifold Learning.
    Yuanyuan Yuan, Qi Pang, and Shuai Wang. USENIX Security 2022 [paper]
  • SoK: Demystifying Binary Lifters Through the Lens of Downstream Applications.
    Zhibo Liu, Yuanyuan Yuan, Shuai Wang, and Yuyan Bao. IEEE Security & Privacy 2022 [paper]
  • SanRazor: Reducing Redundant Sanitizer Checks in C/C++ Programs.
    Jiang Zhang, Shuai Wang, Manuel Rigger, Pingjia He, and Zhendong Su. OSDI 2021 [paper]
  • Perception Matters: Detecting Perception Failures of VQA Models Using Metamorphic Testing.
    Yuanyuan Yuan, Shuai Wang, Mingyue Jiang, and Tsong Yueh Chen. CVPR 2021 [paper]
  • Private Image Reconstruction from System Side Channels Using Generative Models.
    Yuanyuan Yuan, Shuai Wang, and Junping Zhang. ICLR 2021 [paper]
  • F2ED-Learning: Good Fences Make Good Neighbors.
    Lun Wang, Qi Pang, Shuai Wang, and Dawn Song. SpicyFL 2020 at NeurIPS 2020
  • Generating Effective Software Obfuscation Sequences with Reinforcement Learning.
    Huaijin Wang, Shuai Wang, Dongpeng Xu, Xiangyu Zhang, and Xiao Liu. IEEE TDSC 2020 [preprint]
  • Metamorphic Object Insertion for Testing Object Detection Systems.
    Shuai Wang and Zhendong Su. ASE 2020. [paper]
  • Metamorphic Testing and Certified Mitigation of Fairness Violations in NLP Models.
    Pingchuan Ma, Shuai Wang, and Jin Liu. IJCAI 2020.
  • How Far We Have Come: Testing Decompilation Correctness of C Decompilers.
    Zhibo Liu and Shuai Wang. ISSTA 2020.
  • Quantitative Assessment on the Limitations of Code Randomization for Legacy Binaries.
    Pei Wang, Jinquan Zhang, Shuai Wang, and Dinghao Wu. IEEE EuroS&P 2020.
  • Detecting Nondeterministic Payment Bugs in Ethereum Smart Contracts.
    Shuai Wang, Chengyu Zhang, and Zhendong Su. OOPSLA 2019.
  • Identifying Cache-Based Side Channels through Secret-Augmented Abstract Interpretation.
    Shuai Wang, Yuyan Bao, Xiao Liu, Pei Wang, Danfeng Zhang, and Dinghao Wu. USENIX Security 2019. [Extended Version]
  • Automatic Grading of Programming Assignments: A Formal Semantics Based Approach.
    Xiao Liu, Shuai Wang, Pei Wang, and Dinghao Wu. ICSE 2019, SEET Track.
  • Large-Scale Third-party Library Detection in Android Markets.
    Menghao Li, Pei Wang, Wei Wang, Shuai Wang, Dinghao Wu, Jian Liu, Rui Xue, Wei Huo and Wei Zou. IEEE TSE .
  • Software Protection on the Go: A Large-Scale Empirical Study on Mobile App Obfuscation.
    Pei Wang, Qinkun Bao, Li Wang, Shuai Wang, Zhaofeng Chen, Tao Wei and Dinghao Wu. ICSE 2018.
  • RedDroid: Android Application Redundancy Customization Based on Static Analysis.
    Yufei Jiang, Qinkun Bao, Shuai Wang, Xiao Liu and Dinghao Wu. ISSRE 2018.
  • Binary Code Retrofitting and Hardening Using SGX.
    Shuai Wang, Wenhao Wang, Qinkun Bao, Pei Wang, XiaoFeng Wang, and Dinghao Wu. FEAST 2017, co-located with CCS 2017.
  • In-Memory Fuzzing for Binary Code Similarity Analysis.
    Shuai Wang and Dinghao Wu. ASE 2017.
  • Turing Obfuscation.
    Yan Wang, Shuai Wang, Pei Wang, and Dinghao Wu. SecureComm 2017.
  • Lambda Obfuscation.
    Pengwei Lan, Pei Wang, Shuai Wang, and Dinghao Wu. SecureComm 2017.
  • Composite Software Diversification.
    Shuai Wang, Pei Wang, and Dinghao Wu. ICSME 2017.
  • Semantics-Aware Machine Learning for Function Recognition in Binary Code.
    Shuai Wang, Pei Wang, and Dinghao Wu. ICSME 2017.
  • CacheD: Identifying Cache-Based Timing Channels in Production Software.
    Shuai Wang, Pei Wang, Xiao Liu, Danfeng Zhang, and Dinghao Wu. USENIX Security 2017.
  • LibD: Scalable and Precise Third-party Library Detection in Android Markets.
    Menghao Li, Wei Wang, Pei Wang, Shuai Wang, Dinghao Wu, Jian Liu, Rui Xue, and Wei Huo. ICSE 2017.
  • From Physical to Cyber: Escalating Protection for Personalized Auto Insurance.
    Le Guan, Jun Xu, Shuai Wang, Xinyu Xing, Lin Lin, Heqing Huang, Peng Liu, and Wenke Lee. SenSys 2016.
  • Uroboros: Instrumenting Stripped Binaries with Static Reassembling.
    Shuai Wang, Pei Wang, and Dinghao Wu. SANER 2016.
  • Translingual Obfuscation.
    Pei Wang, Shuai Wang, Jiang Ming, Yufei Jiang, and Dinghao Wu. EuroS&P 2016. [Extended Version]
  • Reassembleable Disassembling.
    Shuai Wang, Pei Wang, and Dinghao Wu. USENIX Security '15. [Code Release]