Hi, I'm Jingjing Wang .

A
Self-driven, quick starter, passionate for solving a complex and challenging real-world problems.
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About

I am a undergraduate student of Zhejiang University major in Information Security. I enjoy problem-solving and coding and believe that the most important thing is to enjoy the process but not the end. I have worked on technologies like Python, MySQL, C, C++, Verilog, Chisel, Riscv and Mips during my first three school years. I am passionate about diving into complex problems and fully enjoy the process to think , explore and handle. I'm always on the way finding what I truly love and strive to bring 100% to the work I do.

  • Languages: Python, C, C++, Bash, Verilog, Chisel
  • Databases: MySQL
  • Libraries: NumPy, Pandas, Matplotlib
  • Frameworks: Qt, PyTorch
  • Tools & Technologies: Git, Docker, Qemu, Verilator

Projects

music streaming app
MMM(Marvelous Mips Machine)

A five-stage pipeline Mips32 CPU based on Chisel

Accomplishments
  • Award: NSCSCC2022 group second prize
  • Tools: Chisel, Verilog, Qemu, Verilator
  • Sequential dual-issue five-stage pipeline, 110MHz time frequency.
  • Branch prediction based on BHT and BTB with 88.24% prediction accuracy.
  • QMC (Quine-McCluskey) minimalize the logic of decoder.
  • Pipeline Cache read and write.
quiz app
Purifier

A defense method against Data Inference in Deep Learning

Accomplishments
  • TDSC underreview
  • Tools: Python, Pytorch, Numpy, Pandas
  • Core Components of CVAE to mitigate the difference in statistical distribution between members and non-members.
  • Apply Label Swapper to defend against label-only attack.
Screenshot of web app
Semantic Communication Security

Explore classic adversarial attack under semantic communication.

Accomplishments
  • Explorative project for course computer network
  • Tools: Python, Pytorch, Matplotlib
  • With simple datasets MNIST, deep-learning enabled semantic communication network can also leak privacy.
Screenshot of web app
Generative Model Security

Distribution Inference Attack against Generative Models

Accomplishments
  • Aiming: CCS underreview
  • Tools: Python, Pytorch, Matplotlib
  • Whether the newly populated diffusion model or the classic GAN, they'll leak training information beyond comprehension.
  • We work on the granularity of data distribution or what we say class feature, aiming at proposing a more general attack.

Skills

Languages and Databases

Python
MySQL
Chisel
Shell Scripting
C++

Libraries

NumPy
Pandas
matplotlib
pwntools

Frameworks

PyTorch
QT

Other

Git
Qemu
Docker
Verilator
CodeQL

Education

Zhejiang University

Hangzhou, Zhejiang, China

Major: Information Security, College of Computer and Science
GPA: 4.73/5.0 (3.99/4.0)
Rank: 2/723 (Information category of engineering for first semester), 1/27 (Information Security for following semesters)
English: CET4-588, CET6-593

    Relevant Courseworks:

    • Advanced/Basic Data Structures and Algorithms
    • Computer Organizations(Logic Design, Computer Architectures, Operating System)
    • Database
    • Computer Network
    • Software Security, Encryptography, Computer Network Security Theory and Practice
    • Corporate Finance, Microeconomics, Macroeconomics

Contact

+86 13336016402

3200104880@zju.edu.com

github.com/23wjj