5 citations · 6 across the 4 of their papers we have counts for
4 papers
S-BDT: Distributed Differentially Private Boosted Decision Trees
Thorsten Peinemann, Moritz Kirschte, Joshua Stock +2
We introduce S-BDT: a novel -differentially private distributed gradient boosted decision tree (GBDT) learner that improves the protection of single training data…
LoVe is in the Air -- Location Verification of ADS-B Signals using Distributed Public Sensors
Johanna Ansohn McDougall, Alessandro Brighente, Willi Großmann +3
The Automatic Dependant Surveillance-Broadcast (ADS-B) message scheme was designed without any authentication or encryption of messages in place. It is therefore easily possible to…
The Applicability of Federated Learning to Official Statistics
Joshua Stock, Oliver Hauke, Julius Weißmann +1
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 method…
Lessons Learned: Defending Against Property Inference Attacks
Joshua Stock, Jens Wettlaufer, Daniel Demmler +1
This work investigates and evaluates multiple defense strategies against property inference attacks (PIAs), a privacy attack against machine learning models. Given a trained machin…