no code implementations • 28 Jul 2023 • Joshua Stock, Oliver Hauke, Julius Weißmann, Hannes Federrath
This work investigates the potential of Federated Learning (FL) for official statistics and shows how well the performance of FL models can keep up with centralized learning methods. F L is particularly interesting for official statistics because its utilization can safeguard the privacy of data holders, thus facilitating access to a broader range of data.
no code implementations • 18 May 2022 • Joshua Stock, Jens Wettlaufer, Daniel Demmler, Hannes Federrath
Extensive experiments with property unlearning show that while it is very effective when defending target models against specific adversaries, property unlearning is not able to generalize, i. e., protect against a whole class of PIAs.
no code implementations • 21 Mar 2016 • Dominik Herrmann, Max Maaß, Hannes Federrath
The Domain Name System (DNS) does not provide query privacy.
Cryptography and Security