2 papers
cs.LG2021
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…
cs.LG2021
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…