Open-Set Source Attribution for Panchromatic Satellite Imagery.

In the last few years, several companies started offering the possibility of buying different kinds of overhead images acquired by satellites orbiting around the planet. This market is interesting for several customers, from those who simply fancy a shot of their house from space, to those aiming to acquire strategic information on portions of land. Due to the sensitive nature of this data, which can be maliciously altered by anyone, the forensic community has started investigating methodologies to verify overhead imagery authenticity and integrity. Within this context, in this paper we investigate the possibility of using Convolutional Neural Networks (CNNs) to attribute a panchromatic satellite image to the satellite used to acquire it. In our investigation we tackle both closed-set and, adapting Deep Ensemble (DE) and Monte Carlo Dropout (MCD) techniques, open-set image attribution problems.