89 citations · 191 across the 14 of their papers we have counts for
6 papers · 1 filter
Conflicting Privacy Preference Signals in the Wild
Maximilian Hils, Daniel W. Woods, Rainer Böhme
Privacy preference signals allow users to express preferences over how their personal data is processed. These signals become important in determining privacy outcomes when they re…
Who are the arbitrageurs? Empirical evidence from Bitcoin traders in the Mt. Gox exchange platform
Pietro Saggese, Alessandro Belmonte, Nicola Dimitri +2
We mine the leaked history of trades on Mt. Gox, the dominant Bitcoin exchange from 2011 to early 2014, to detect the triangular arbitrage activity conducted within the platform. T…
Privacy Preference Signals: Past, Present and Future
Maximilian Hils, Daniel W. Woods, Rainer Böhme
Privacy preference signals are digital representations of how users want their personal data to be processed. Such signals must be adopted by both the sender (users) and intended r…
iNNformant: Boundary Samples as Telltale Watermarks
Alexander Schlögl, Tobias Kupek, Rainer Böhme
Boundary samples are special inputs to artificial neural networks crafted to identify the execution environment used for inference by the resulting output label. The paper presents…
More Real than Real: A Study on Human Visual Perception of Synthetic Faces
Federica Lago, Cecilia Pasquini, Rainer Böhme +3
Deep fakes became extremely popular in the last years, also thanks to their increasing realism. Therefore, there is the need to measures human's ability to distinguish between real…
Forensicability of Deep Neural Network Inference Pipelines
Alexander Schlögl, Tobias Kupek, Rainer Böhme
We propose methods to infer properties of the execution environment of machine learning pipelines by tracing characteristic numerical deviations in observable outputs. Results from…