KDD 2025 Tutorial:

Model Extraction Attack and Defense for Large Language Models: Recent Advances, Challenges, and Future Prospectives

🥹 Welcome to the official tutorial page for our KDD 2025 Tutorial on Model Extraction Attacks and Defenses for Large Language Models (LLMs), presented at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025). This repository contains the static website source code that was presented during the tutorial session. It is intended to serve not only as a reference for attendees but also as a template for future tutorials, workshops, and academic event websites. For any questions or suggestions about this webpage template, please contact Lincan Li.

---

🌐 Tutorial Website

🔗 Live Website: https://labrai.github.io/KDD2025_Tutorial/

📅 Conference: SIGKDD 2025

⌚️ Time: Sunday, August 3, 01:00 PM - 04:00 PM (ET).

📍 Location: Room xxx, Metro Toronto Convention Centre, Toronto, Canada.

---

Repository Structure

KDD2025_Tutorial/
├── index.html                # Main landing page
├── assets/                   # Images, icons, and figures
├── css/                      # Website styling
├── js/                       # Interactive elements and animations
├── data/                     # Example datasets or JSON resources (if any)
├── notebooks/                # Jupyter notebooks for hands-on exercises
├── slides/                   # Tutorial presentation slides (PDF/PPTX)
├── references/               # Additional reading materials
└── README.md                 # This file

---

🚀 Getting Started

1️⃣ Clone this repository

git clone https://github.com/yourusername/KDD2025_Tutorial.git
cd KDD2025_Tutorial

2️⃣ Run locally

You can open the site directly:

open index.html

Or use a simple HTTP server (Python example):

python3 -m http.server 8080

Then open http://localhost:8080 in your browser.

3️⃣ Deploy (optional)

Easily deploy your tutorial website to:

• Netlify: drag and drop the folder
• GitHub Pages: push to main and enable Pages in repo settings
• Vercel: vercel deploy

---

📚 Tutorial Materials

• 📄 Slides: Available under slides/
• 💻 Jupyter Notebooks: In the notebooks/ folder
• 🧪 Code Demos: See the js/ directory for live demos
• 🔗 Supplementary Links: Provided in the Resources section of the website

---

👨‍🏫 Tutorial Instructors

Name	Affiliation	Website
[Instructor 1]	[Institution]	[URL]
[Instructor 2]	[Institution]	[URL]
[Instructor 3]	[Institution]	[URL]

---

🧾 Citation

If you use or reference this tutorial related resource in your research, please kindly cite:

@inproceedings{zhao2025survey,
  title={A survey on model extraction attacks and defenses for large language models},
  author={Zhao, Kaixiang and Li, Lincan and Ding, Kaize and Gong, Neil Zhenqiang and Zhao, Yue and Dong, Yushun},
  booktitle={Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 2},
  pages={6227--6236},
  year={2025}
}

---

🤝 Contributing

We welcome improvements to this Template (typo fixes, translation, accessibility, etc.).

1. Fork the repository
2. Create a new branch
3. Commit your changes
4. Submit a pull request

---

📬 Contact

For questions or feedback about this Template, please contact: 📧 [Lincan Li] or open an issue in this repository.

---

💡 Quick Links

• KDD 2025 Official Website
• ACM Digital Library
• Previous KDD Tutorials

---