Nils Lukas
Nils Lukas
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Cited by
Cited by
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
N Lukas, Y Zhang, F Kerschbaum
The Ninth International Conference on Learning Representations (ICLR 2021), 2021
On the Robustness of Backdoor-based Watermarking in Deep Neural Networks
M Shafieinejad, N Lukas, J Wang, X Li, F Kerschbaum
Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia …, 2021
Analyzing Leakage of Personally Identifiable Information in Language Models
N Lukas, A Salem, R Sim, S Tople, L Wutschitz, S Zanella-Béguelin
2023 IEEE Symposium on Security and Privacy (S&P), 2023
Sok: How Robust is Image Classification Deep Neural Network Watermarking?
N Lukas, E Jiang, X Li, F Kerschbaum
2022 IEEE Symposium on Security and Privacy (SP), 787-804, 2022
Differentially private two-party set operations
B Kacsmar, B Khurram, N Lukas, A Norton, M Shafieinejad, Z Shang, ...
2020 IEEE European Symposium on Security and Privacy (EuroS&P), 390-404, 2020
Practical Over-Threshold Multi-Party Private Set Intersection
RA Mahdavi, T Humphries, B Kacsmar, S Krastnikov, N Lukas, ...
Annual Computer Security Applications Conference, 772-783, 2020
PTW: Pivotal Tuning Watermarking for Pre-Trained Image Generators
N Lukas, F Kerschbaum
The 32nd USENIX Security Symposium, 2023
SunFlower: A new solar tower simulation method for use in field layout optimization
P Richter, G Heiming, N Lukas, M Frank
AIP Conference Proceedings 2033 (1), 2018
Leveraging optimization for adaptive attacks on image watermarks
N Lukas, A Diaa, L Fenaux, F Kerschbaum
The Twelfth International Conference on Learning Representations (ICLR'24), 2024
Fast and private inference of deep neural networks by co-designing activation functions
A Diaa, L Fenaux, T Humphries, M Dietz, F Ebrahimianghazani, ...
The 33rd USENIX Security Symposium, 2023
Privacy-Preserving Machine Learning [Cryptography]
F Kerschbaum, N Lukas
IEEE Security & Privacy 21 (6), 90-94, 2023
Pick your Poison: Undetectability versus Robustness in Data Poisoning Attacks against Deep Image Classification
N Lukas, F Kerschbaum
arXiv preprint arXiv:2305.09671, 2023
Universal Backdoor Attacks
B Schneider, N Lukas, F Kerschbaum
The Twelfth International Conference on Learning Representations (ICLR'24), 2024
Analyzing Threats of Large-Scale Machine Learning Systems
N Lukas
University of Waterloo, 2024
PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting
RA Mahdavi, N Lukas, F Ebrahimianghazani, T Humphries, B Kacsmar, ...
arXiv preprint arXiv:2310.14565, 2023
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