LEAF: A Faster Secure Search Algorithm via Localization, Extraction, and Reconstruction. - Rui Wen 002; Yu Yu 001; Xiang Xie; Yang Zhang 016 (CCS, 2020)

Node-Level Membership Inference Attacks Against Graph Neural Networks. - Xinlei He 001; Rui Wen 002; Yixin Wu 001; Michael Backes 001; Yun Shen; Yang Zhang 016 (CoRR, 2021)

Dynamic Backdoor Attacks Against Machine Learning Models. - Ahmed Salem 001; Rui Wen 002; Michael Backes 001; Shiqing Ma; Yang Zhang 016 (EuroS&P, 2022)

ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models. - Yugeng Liu; Rui Wen 002; Xinlei He 001; Ahmed Salem 001; Zhikun Zhang 001; Michael Backes 001; Emiliano De Cristofaro; Mario Fritz; Yang Zhang 016 (USENIX Security Symposium, 2022)

Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning? - Rui Wen 002; Zhengyu Zhao 001; Zhuoran Liu 001; Michael Backes 001; Tianhao Wang 001; Yang Zhang 016 (ICLR, 2023)

Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning. - Rui Wen 002; Tianhao Wang 001; Michael Backes 001; Yang Zhang 016; Ahmed Salem 001 (CoRR, 2023)

Membership Inference Attacks Against In-Context Learning. - Rui Wen 002; Zheng Li 023; Michael Backes 001; Yang Zhang 016 (CCS, 2024)

Games and Beyond: Analyzing the Bullet Chats of Esports Livestreaming. - Yukun Jiang 001; Xinyue Shen 001; Rui Wen 002; Zeyang Sha; Junjie Chu 002; Yugeng Liu; Michael Backes 001; Yang Zhang 016 (ICWSM, 2024)

Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. - Edoardo Debenedetti; Javier Rando; Daniel Paleka; Silaghi Fineas Florin; Dragos Albastroiu; Niv Cohen; Yuval Lemberg; Reshmi Ghosh; Rui Wen 002; Ahmed Salem 001; Giovanni Cherubin; Santiago Zanella-Béguelin; et al. (NeurIPS, 2024)

Quantifying Privacy Risks of Prompts in Visual Prompt Learning. - Yixin Wu 001; Rui Wen 002; Michael Backes 001; Pascal Berrang; Mathias Humbert; Yun Shen; Yang Zhang 016 (USENIX Security Symposium, 2024)

Instruction Backdoor Attacks Against Customized LLMs. - Rui Zhang 086; Hongwei Li 001; Rui Wen 002; Wenbo Jiang 001; Yuan Zhang 006; Michael Backes 001; Yun Shen; Yang Zhang 016 (USENIX Security Symposium, 2024)

Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models. - Minxing Zhang; Ning Yu 006; Rui Wen 002; Michael Backes 001; Yang Zhang 016 (WACV, 2024)

Rapid Adoption, Hidden Risks: The Dual Impact of Large Language Model Customization. - Rui Zhang 086; Hongwei Li 001; Rui Wen 002; Wenbo Jiang 001; Yuan Zhang 006; Michael Backes 001; Yun Shen; Yang Zhang 016 (CoRR, 2024)

Efficient Data-Free Model Stealing with Label Diversity. - Yiyong Liu; Rui Wen 002; Michael Backes 001; Yang Zhang 016 (CoRR, 2024)

Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm? - Rui Wen 002; Michael Backes 001; Yang Zhang 016 (NDSS, 2025)

Peering Behind the Shield: Guardrail Identification in Large Language Models. - Ziqing Yang 002; Yixin Wu 001; Rui Wen 002; Michael Backes 001; Yang Zhang 016 (CoRR, 2025)

SoK: Data Reconstruction Attacks Against Machine Learning Models: Definition, Metrics, and Benchmark. - Rui Wen 002; Yiyong Liu; Michael Backes 001; Yang Zhang 016 (CoRR, 2025)