prof_pic.jpg

Room 3505

Academic Building

Dongdong She

Assistant Professor
Department of Computer Science and Engineering
Hong Kong University of Science and Technology
dongdong@cse.ust.hk

Google Scholar, GitHub, Twitter

Drop me an email if you are interested in working with me!

I received my Ph.D. at the Department of Computer Science, Columbia University working with Suman Jana and Baishakhi Ray. Before coming to Columbia, I worked with Zhiyun Qian on Android Security at the University of California, Riverside. I earned my bachelor’s degree at Huazhong University of Science and Technology.

I am broadly interested in security and machine learning. Particularly, I focus on applying data-driven approaches (e.g., large language models, machine learning, optimization) to solve security problems. Current research projects include:

  • Neural-Symbolic Software Testing: advance the state-of-the-art in automated software testing techniques such as fuzzing, symbolic execution, and formal verification through developing algorithms and tools that combine neural and symbolic approaches.
  • Emerging Applications: adopt data-driven approaches to solve security issues in high-impactful domains such as autonomous driving, ML system, and smart contracts.

Publications

2023

  1. IEEE S&P
    Precise Detection of Kernel Data Races with Probabilistic Lockset Analysis.
    Gabriel Ryan, Abhishek Shah,  Dongdong She, and Suman Jana
    IEEE Symposium on Security and Privacy (S&P 2023)
    PDF

2022

  1. IEEE S&P
    Effective Seed Scheduling for Fuzzing with Graph Centrality Analysis.
    Dongdong She, Abhishek Shah, and Suman Jana
    IEEE Symposium on Security and Privacy (S&P 2022)
    PDF Code
  2. CCS
    MC2: Rigorous and Efficient Directed Greybox Fuzzing.
    Abhishek Shah,  Dongdong She, Samanway Sadhu, Krish Singal, Peter Coffman, and Suman Jana
    ACM SIGSAC Conference on Computer and Communications Security (CCS 2022)
    Best Paper Award Runner-Up
    PDF Code
  3. FSE
    NeuDep: Neural Binary Memory Dependence Analysis
    Kexin Pei,  Dongdong She, Michael Wang, Scott Geng, Zhou Xuan, Yaniv David, Junfeng Yang, Suman Jana, and Baishakhi Ray
    ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2022)
    PDF Code

2021

  1. Security
    Fine Grained Dataflow Tracking with Proximal Gradients
    Gabriel Ryan, Abhishek Shah,  Dongdong She, Koustubha Bhat, and Suman Jana
    USENIX Conference on Security Symposium (Security 2021)
    PDF

2020

  1. Security
    On Training Robust PDF Malware Classifiers
    Yizheng Chen, Shiqi Wang,  Dongdong She, and Suman Jana
    USENIX Conference on Security Symposium (Security 2020)
    PDF Code
  2. FSE
    MTFuzz: Fuzzing with a Multi-Task Neural Network
    Dongdong She, Rahul Krishna, Lu Yan, Suman Jana, and Baishakhi Ray
    ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2020)
    PDF Code
  3. IEEE S&P
    Neutaint: Efficient Dynamic Taint Analysis with Neural Networks
    Dongdong She, Yizheng Chen, Abhishek Shah, Baishakhi Ray, and Suman Jana
    IEEE Symposium on Security and Privacy (S&P 2020)
    PDF

2019

  1. IEEE S&P
    NEUZZ: Efficient Fuzzing with Neural Program Smoothing
    Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, and Suman Jana
    IEEE Symposium on Security and Privacy (S&P 2019)
    Finalist in 2019 NYU CSAW Applied Research Competition
    PDF Code

2016

  1. CCS
    Android ION Hazard: The Curse of Customizable Memory Management System
    Hang Zhang,  Dongdong She, and Zhiyun Qian
    ACM SIGSAC Conference on Computer and Communications Security (CCS 2016)
    PDF

2015

  1. CCS
    Android Root and Its Providers: A Double-Edged Sword
    Hang Zhang,  Dongdong She, and Zhiyun Qian
    ACM SIGSAC Conference on Computer and Communications Security (CCS 2015)
    PDF