4 citations · 4 across the 5 of their papers we have counts for
6 papers
Understanding the "Why": Investigating the Design of Privacy Support Tools (PSTs) through the Lens of Psychological Needs
Sara Hahn, Verena Zimmermann, Simon Althaus +4
Privacy Support Tools (PSTs) help users control their digital data, but face low adoption due to resignation and overwhelm. While current regulations aim to enhance privacy control…
WOOTdroid: Whole-system Online On-device Tracing for Android
Simon Althaus, Nikolaos Alexopoulos, Max Mühlhäuser +2
System auditing on Android faces two problems. First, existing syscall tracers lose events under load, silently overwriting entries faster than a user space reader can drain them.…
Mitigating Intersection Attacks in Anonymous Microblogging
Sarah Abdelwahab Gaballah, Thanh Hoang Long Nguyen, Lamya Abdullah +2
Anonymous microblogging systems are known to be vulnerable to intersection attacks due to network churn. An adversary that monitors all communications can leverage the churn to lea…
Federated Learning Attacks Revisited: A Critical Discussion of Gaps, Assumptions, and Evaluation Setups
Aidmar Wainakh, Ephraim Zimmer, Sandeep Subedi +5
Federated learning (FL) enables a set of entities to collaboratively train a machine learning model without sharing their sensitive data, thus, mitigating some privacy concerns. Ho…
User-Level Label Leakage from Gradients in Federated Learning
Aidmar Wainakh, Fabrizio Ventola, Till Müßig +6
Federated learning enables multiple users to build a joint model by sharing their model updates (gradients), while their raw data remains local on their devices. In contrast to the…
PEEPLL: Privacy-Enhanced Event Pseudonymisation with Limited Linkability
Ephraim Zimmer, Christian Burkert, Tom Petersen +1
Pseudonymisation provides the means to reduce the privacy impact of monitoring, auditing, intrusion detection, and data collection in general on individual subjects. Its applicatio…