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Lukas Bieringer
Lukas Bieringer
Head of Policy & Grants, QuantPi
Verified email at quantpi.com
Title
Cited by
Cited by
Year
Industrial practitioners' mental models of adversarial machine learning
L Bieringer, K Grosse, M Backes, B Biggio, K Krombholz
Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022), 97-116, 2022
192022
Machine learning security in industry: A quantitative survey
K Grosse, L Bieringer, TR Besold, B Biggio, K Krombholz
IEEE Transactions on Information Forensics and Security 18, 1749-1762, 2023
152023
Mental models of adversarial machine learning
L Bieringer, K Grosse, M Backes, B Biggio, K Krombholz
arXiv preprint arXiv:2105.03726, 2021
62021
Why do so?”-A Practical Perspective on Machine Learning Security
K Grosse, L Bieringer, TR Besold, B Biggio, K Krombholz
Int. Conf. Machin. Learn.: New Frontiers of Adversarial Machine Learning, 2022
42022
Towards more Practical Threat Models in Artificial Intelligence Security
K Grosse, L Bieringer, TR Besold, A Alahi
arXiv preprint arXiv:2311.09994, 2023
12023
When Your AI Becomes a Target: AI Security Incidents and Best Practices
K Grosse, L Bieringer, TR Besold, B Biggio, A Alahi
Proceedings of the AAAI Conference on Artificial Intelligence 38 (21), 23041 …, 2024
2024
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