Secure multi-party computation of differentially private median J Böhler, F Kerschbaum 29th USENIX Security Symposium (USENIX Security 20), 2147-2164, 2020 | 42 | 2020 |
Secure multi-party computation of differentially private heavy hitters J Böhler, F Kerschbaum Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 35 | 2021 |
Secure sublinear time differentially private median computation J Böhler, F Kerschbaum 27th Annual Network and Distributed System Security Symposium, {NDSS} 2020, 2020 | 31 | 2020 |
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 | 24* | 2017 |
Tracking privacy budget with distributed ledger D Bernau, F Hahn, J Boehler US Patent 10,380,366, 2019 | 18 | 2019 |
Differential privacy and outlier detection within a non-interactive model J Boehler, D Bernau, F Kerschbaum US Patent 10,445,527, 2019 | 15 | 2019 |
Secure multi-party computation of differentially private heavy hitters J Boehler US Patent App. 17/357,096, 2023 | 10 | 2023 |
Efficient distributed privacy-preserving computations J Boehler US Patent 12,081,644, 2024 | 7 | 2024 |
Input Secrecy & Output Privacy: Efficient Secure Computation of Differential Privacy Mechanisms J Böhler Karlsruhe Institute of Technology, Germany, 2021 | 2 | 2021 |
Privacy-preserving demand estimation across companies J Boehler US Patent App. 18/055,110, 2024 | | 2024 |
Secure multiparty differentially private median computation J Boehler, F Kerschbaum US Patent 11,861,038, 2024 | | 2024 |
Secure data processing in untrusted environments B Fuhry, J Boehler US Patent App. 17/819,292, 2022 | | 2022 |
Secure data processing in untrusted environments B Fuhry, J Boehler US Patent 11,449,624, 2022 | | 2022 |
Secure Computation of Differentially Private Mechanisms J Böhler Encyclopedia of Cryptography, Security and Privacy, 1-4, 2021 | | 2021 |