51 citations · 148 across the 13 of their papers we have counts for
3 papers · 1 filter
Attesting Distributional Properties of Training Data for Machine Learning
Vasisht Duddu, Anudeep Das, Nora Khayata +3
The success of machine learning (ML) has been accompanied by increased concerns about its trustworthiness. Several jurisdictions are preparing ML regulatory frameworks. One such co…
ExTRUST: Reducing Exploit Stockpiles with a Privacy-Preserving Depletion System for Inter-State Relationships
Thomas Reinhold, Philipp Kuehn, Daniel Günther +2
Cyberspace is a fragile construct threatened by malicious cyber operations of different actors, with vulnerabilities in IT hardware and software forming the basis for such activiti…
WW-FL: Secure and Private Large-Scale Federated Learning
Felix Marx, Thomas Schneider, Ajith Suresh +3
Federated learning (FL) is an efficient approach for large-scale distributed machine learning that promises data privacy by keeping training data on client devices. However, recent…