Monte carlo and reconstruction membership inference attacks against generative models B Hilprecht, M Härterich, D Bernau
Proceedings on Privacy Enhancing Technologies, 2019
163 2019 Anonymization techniques to protect data C Hebert, D Bernau, A Lahouel
US Patent 10,628,608, 2020
60 2020 Assessing differentially private deep learning with membership inference D Bernau, PW Grassal, J Robl, F Kerschbaum
arXiv preprint arXiv:1912.11328, 2019
28 2019 Comparing local and central differential privacy using membership inference attacks D Bernau, J Robl, PW Grassal, S Schneider, F Kerschbaum
IFIP Annual Conference on Data and Applications Security and Privacy, 22-42, 2021
23 2021 The influence of differential privacy on short term electric load forecasting G Eibl, K Bao, PW Grassal, D Bernau, H Schmeck
Energy Informatics 1 (Suppl 1), 48, 2018
20 2018 Privacy-preserving outlier detection for data streams J Böhler, D Bernau, F Kerschbaum
IFIP Annual Conference on Data and Applications Security and Privacy, 225-238, 2017
19 2017 Tracking privacy budget with distributed ledger D Bernau, F Hahn, J Boehler
US Patent 10,380,366, 2019
16 2019 Differential privacy and outlier detection within a non-interactive model J Boehler, D Bernau, F Kerschbaum
US Patent 10,445,527, 2019
14 2019 On the Privacy–Utility Trade-Off in Differentially Private Hierarchical Text Classification D Wunderlich, D Bernau, F Aldà, J Parra-Arnau, T Strufe
Applied Sciences 12 (21), 11177, 2022
10 2022 Assessing Differentially Private Variational Autoencoders under Membership Inference D Bernau, J Robl, F Kerschbaum
IFIP Annual Conference on Data and Applications Security and Privacy, 3-14, 2022
7 2022 Interpretability Framework for Differentially Private Deep Learning D Bernau, PW Grassal, H Keller, M Haerterich
US Patent App. 17/086,244, 2022
7 2022 Quantifying identifiability to choose and audit in differentially private deep learning D Bernau, G Eibl, PW Grassal, H Keller, F Kerschbaum
arXiv preprint arXiv:2103.02913, 2021
6 2021 Providing differentially private data with causality preservation W Beskorovajnov, D Bernau
US Patent 10,423,781, 2019
6 2019 Selective access for supply chain management in the cloud A Tueno, F Kerschbaum, D Bernau, S Foresti
2017 IEEE Conference on Communications and Network Security (CNS), 476-482, 2017
5 2017 Quantifying Identifiability to Choose and Audit ǫ in Differentially Private Deep Learning D Bernau, G Eibl, PW Grassal, H Keller, F Kerschbaum
Proceedings of the Conference on Very Large Databases, 2021
4 2021 Privacy preserving smart metering D Bernau, PW Grassal, F Kerschbaum
US Patent 10,746,567, 2020
4 2020 Differential privacy to prevent machine learning model membership inference D Bernau, J Robl, PW Grassal, F Kerschbaum
US Patent 11,449,639, 2022
3 2022 Reconstruction and membership inference attacks against generative models B Hilprecht, M Härterich, D Bernau
arXiv preprint arXiv:1906.03006, 2019
3 2019 Accurately identifying members of training data in variational autoencoders by reconstruction error B Hilprecht, D Bernau, M Haerterich
US Patent 11,501,172, 2022
2022 Computer systems for detecting training data usage in generative models M Haerterich, B Hilprecht, D Bernau
US Patent 11,366,982, 2022
2022