Publikationen

Krueger, Stephanie und Rebecca D. Frank. 2024. Are we practicing what we preach? Towards greater transborder inclusivity in Information Science systematic reviews. In: Sserwanga, I., et al. Wisdom, Well-Being, Win-Win. iConference 2024. Lecture Notes in Computer Science, vol 14598. Springer, Cham. https://doi.org/10.1007/978-3-031-57867-0_6

Hoster, Johannes und Sara Al-Sayed, Felix Biessmann, Alexander Glaser, Kristian Hildebrand, Igor Moric, und Tuong Vy Nguyen. 2023. Using Game Engines and Machine Learning to Create Synthetic Satellite Imagery for a Nuclear Verification Tabletop Exercise. In: INMM & ESARDA Joint Annual Meeting. Wien, Mai 2023. Link.

Nguyen, Tuong Vy, Alexander Glaser und Felix Biessmann. 2023. Generating Synthetic Satellite Imagery with Deep-Learning Text-to-Image Models: Technical Challenges and Implications for Monitoring and Verification. In: INMM & ESARDA Joint Annual Meeting. Wien, Mai 2023. Link.

Abstract

In a future where digital data from from a variety of sources are abundant and widely available to non-governmental experts and independent analysts, and where virtually any type of digital media can be generated in ways that can make them effectively indistinguishable from real data, issues of data authentication in monitoring and verification deserve a careful and systematic analysis. In this project, funded by the Deutsche Stiftung Friedensforschung (German Foundation for Peace Research), Prof. Dr. Felix Bießmann (Berliner Hochschule für Technik), Prof. Dr. Rebecca D. Frank (University of Tennessee, Knoxville), and Prof. Dr. Alexander Glaser (Princeton University) examine the potential role of citizen-based monitoring and verification for peace and security.

This two-phase research project seeks to systematically assess the long-term opportunities for citizen-based monitoring using the important example of satellite imagery in the context of nuclear monitoring and verification, and to understand the risks and challenges, often enabled by these very same techniques and tools. Leveraging advanced machine-learning techniques to generate synthetic imagery of relevant sites, we can produce dedicated datasets under carefully controlled conditions. This imagery will then be used to develop and examine concrete monitoring scenarios. This will be followed by qualitative interviews and hands-on exercises with focus groups and data users in order to examine future challenges for citizen-based monitoring. We will place a particular emphasis on the possibility of image spoofing and fabricated data, examine broader ethical issues related to persistent earth observation, but also consider safeguards that could make citizen-based monitoring a viable and robust tool in support of peace and security.