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Wilko Henecka
Wilko Henecka
CSIRO's DATA61
Verified email at data61.csiro.au
Title
Cited by
Cited by
Year
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
S Hardy, W Henecka, H Ivey-Law, R Nock, G Patrini, G Smith, B Thorne
arXiv preprint arXiv:1711.10677, 2017
5722017
TASTY: tool for automating secure two-party computations
W Henecka, S K ögl, AR Sadeghi, T Schneider, I Wehrenberg
Proceedings of the 17th ACM conference on Computer and communications …, 2010
4872010
Entity resolution and federated learning get a federated resolution
R Nock, S Hardy, W Henecka, H Ivey-Law, G Patrini, G Smith, B Thorne
arXiv preprint arXiv:1803.04035, 2018
992018
Correcting errors in RSA private keys
W Henecka, A May, A Meurer
Annual Cryptology Conference, 351-369, 2010
732010
Faster secure two-party computation with less memory
W Henecka, T Schneider
Proceedings of the 8th ACM SIGSAC symposium on Information, computer and …, 2013
522013
Strip: Privacy-preserving vector-based routing
W Henecka, M Roughan
2013 21st IEEE International Conference on Network Protocols (ICNP), 1-10, 2013
242013
Automatic generation of sigma-protocols
E Bangerter, T Briner, W Henecka, S Krenn, AR Sadeghi, T Schneider
European Public Key Infrastructure Workshop, 67-82, 2009
232009
Privacy-preserving fraud detection across multiple phone record databases
W Henecka, M Roughan
IEEE Transactions on Dependable and Secure Computing 12 (6), 640-651, 2014
202014
Lossy compression of dynamic, weighted graphs
W Henecka, M Roughan
2015 3rd International Conference on Future Internet of Things and Cloud …, 2015
122015
The impact of record linkage on learning from feature partitioned data
R Nock, S Hardy, W Henecka, H Ivey-Law, J Nabaglo, G Patrini, G Smith, ...
International Conference on Machine Learning, 8216-8226, 2021
92021
Privacy-preserving entity resolution and logistic regression on encrypted data
M Djatmiko, S Hardy, W Henecka, H Ivey-Law, M Ott, G Patrini, G Smith, ...
Private and Secure Machine Learning (PSML), 2017
82017
Fairness-aware privacy-preserving record linkage
D Vatsalan, J Yu, W Henecka, B Thorne
Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS …, 2020
42020
Hyper-parameter optimization for privacy-preserving record linkage
J Yu, J Nabaglo, D Vatsalan, W Henecka, B Thorne
ECML PKDD 2020 Workshops: Workshops of the European Conference on Machine …, 2020
32020
A measure of personal information in mobile data
I Oppermann, J Nabaglo, W Henecka
2020 2nd 6G Wireless Summit (6G SUMMIT), 1-6, 2020
22020
Boosted and differentially private ensembles of decision trees
R Nock, W Henecka
arXiv preprint arXiv:2001.09384, 2020
22020
P-signature-based blocking to improve the scalability of privacy-preserving record linkage
D Vatsalan, J Yu, B Thorne, W Henecka
Data Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS …, 2020
22020
Network management in a world of secrets.
W Henecka
2015
Conversion of real-numbered privacy-preserving problems into the integer domain
W Henecka, N Bean, M Roughan
Information and Communications Security: 14th International Conference …, 2012
2012
On Private Supervised Distributed Learning: Weakly Labeled and without Entity Resolution
S Hardy, W Henecka, R Nock
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Articles 1–19