Schwegmann, AlexanderAlexanderSchwegmannHübner, ClaudiaClaudiaHübner2025-03-252025-03-252024https://publica.fraunhofer.de/handle/publica/48578510.1117/12.3033914Due to the enormous development in the field of artificial intelligence, especially in the area of reconnaissance, detection and recognition, it has become absolutely necessary to think about methods of concealing one's own military units from this new threat. This publication aims to provide an overview of counter ai approaches against enemy reconnaissance, and the possibilities to assess the effectiveness of these methods. It will focus on explainable AI and the camouflaging of key features as well as the possibility of dual attribute adversarial attack camouflage. These are mathematically optimised patterns that drive an AI-based classifier to an incorrect classification or simply suppress the correct classification. We also discuss the robustness of these patterns.enpresentation