On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks. - Masoumeh Shafieinejad; Jiaqi Wang; Nils Lukas; Florian Kerschbaum (CoRR, 2019)

Practical Over-Threshold Multi-Party Private Set Intersection. - Rasoul Akhavan Mahdavi; Thomas Humphries; Bailey Kacsmar; Simeon Krastnikov; Nils Lukas; John A. Premkumar; Masoumeh Shafieinejad; Simon Oya; Florian Kerschbaum; Erik-Oliver Blass (ACSAC, 2020)

Differentially Private Two-Party Set Operations. - Bailey Kacsmar; Basit Khurram; Nils Lukas; Alexander Norton; Masoumeh Shafieinejad; Zhiwei Shang; Yaser Baseri; Maryam Sepehri; Simon Oya; Florian Kerschbaum (EuroS&P, 2020)

Deep Neural Network Fingerprinting by Conferrable Adversarial Examples. - Nils Lukas; Yuxuan Zhang 001; Florian Kerschbaum (ICLR, 2021)

On the Robustness of Backdoor-based Watermarking in Deep Neural Networks. - Masoumeh Shafieinejad; Nils Lukas; Jiaqi Wang; Xinda Li 001; Florian Kerschbaum (IH&MMSec, 2021)

SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version). - Nils Lukas; Edward Jiang; Xinda Li 001; Florian Kerschbaum (CoRR, 2021)

SoK: How Robust is Image Classification Deep Neural Network Watermarking? - Nils Lukas; Edward Jiang; Xinda Li 001; Florian Kerschbaum (SP, 2022)

Analyzing Leakage of Personally Identifiable Information in Language Models. - Nils Lukas; Ahmed Salem 001; Robert Sim; Shruti Tople; Lukas Wutschitz; Santiago Zanella-Béguelin (SP, 2023)

PTW: Pivotal Tuning Watermarking for Pre-Trained Image Generators. - Nils Lukas; Florian Kerschbaum (USENIX Security Symposium, 2023)

Pick your Poison: Undetectability versus Robustness in Data Poisoning Attacks against Deep Image Classification. - Nils Lukas; Florian Kerschbaum (CoRR, 2023)

Privacy-Preserving Machine Learning [Cryptography]. - Florian Kerschbaum; Nils Lukas (IEEE Secur. Priv., 2023)

Leveraging Optimization for Adaptive Attacks on Image Watermarks. - Nils Lukas; Abdulrahman Diaa; Lucas Fenaux; Florian Kerschbaum (ICLR, 2024)

Universal Backdoor Attacks. - Benjamin Schneider; Nils Lukas; Florian Kerschbaum (ICLR, 2024)

Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. - Abdulrahman Diaa; Lucas Fenaux; Thomas Humphries; Marian Dietz; Faezeh Ebrahimianghazani; Bailey Kacsmar; Xinda Li 001; Nils Lukas; Rasoul Akhavan Mahdavi; Simon Oya; Ehsan Amjadian; Florian Kerschbaum (USENIX Security Symposium, 2024)

PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting. - Rasoul Akhavan Mahdavi; Nils Lukas; Faezeh Ebrahimianghazani; Thomas Humphries; Bailey Kacsmar; John A. Premkumar; Xinda Li 001; Simon Oya; Ehsan Amjadian; Florian Kerschbaum (USENIX Security Symposium, 2024)

Optimizing Adaptive Attacks against Content Watermarks for Language Models. - Abdulrahman Diaa; Toluwani Aremu; Nils Lukas (CoRR, 2024)

Mask Image Watermarking. - Runyi Hu; Jie Zhang 073; Shiqian Zhao; Nils Lukas; Jiwei Li 001; Qing Guo 005; Han Qiu 001; Tianwei Zhang 004 (CoRR, 2025)

SPIRIT: Patching Speech Language Models against Jailbreak Attacks. - Amirbek Djanibekov; Nurdaulet Mukhituly; Kentaro Inui; Hanan Aldarmaki; Nils Lukas (CoRR, 2025)

DP-Fusion: Token-Level Differentially Private Inference for Large Language Models. - Rushil Thareja; Preslav Nakov; Praneeth Vepakomma; Nils Lukas (CoRR, 2025)

Mitigating Watermark Stealing Attacks in Generative Models via Multi-Key Watermarking. - Toluwani Aremu; Noor Hussein; Munachiso Nwadike; Samuele Poppi; Jie Zhang; Karthik Nandakumar; Neil Gong 001; Nils Lukas (CoRR, 2025)

BURN: Backdoor Unlearning via Adversarial Boundary Analysis. - Yanghao Su; Jie Zhang 073; Yiming Li 004; Tianwei Zhang 004; Qing Guo 005; Weiming Zhang 001; Nenghai Yu; Nils Lukas; Wenbo Zhou (CoRR, 2025)