Adversarial Examples in Remote Sensing

This paper considers attacks against machine learning algorithms used in remote sensing applications. The remote sensing domain presents a suite of challenges that are not fully addressed by current research focused on natural image data. In this paper we present a new study of adversarial examples in the context of satellite image classification problems. Using a recently curated data set and associated classifier, we provide a preliminary analysis of adversarial examples in settings where the targeted classifier is permitted multiple observations of the same location over time. While our experiments to date are purely digital, our problem setup incorporates a number of practical considerations that an attacker would need to take into account when mounting physical attacks.