Projekt Rechnernetze und IT-Sicherheit I

Newer vehicles broadcast unencrypted C-ITS messages (ITS-G5) containing their position, speed and other attributes several times per second. To protect drivers, vehicles regularly change their pseudonyms. However, community projects such as OpenTrafficMap show that these messages can be captured with low-cost receivers, which raises the question of how effective pseudonym changes are against a passive, distributed observer. The goal of this work is to assess the feasibility of tracking vehicles across pseudonym changes. Using a simulation environment (e.g., Eclipse MOSAIC), the effects of receiver density, the share of vehicles that transmit C-ITS messages and different linking strategies on achievable tracking should be modeled and evaluated. Results may be compared against real-world observations from receiver networks. Possible extensions include evaluating countermeasures. The scope can be adapted to Bachelor, Master or project level; please contact me for further discussion.

GNSS spoofing poses a significant threat to systems relying on accurate positioning, particularly in safety-critical domains such as autonomous driving. However, the evaluation of spoofing detection methods is often limited by the lack of standardized benchmark datasets. This project addresses this gap by designing and implementing a benchmark dataset for GNSS spoofing detection systems. The dataset includes diverse and realistic spoofing scenarios with well-defined ground truth, enabling systematic and reproducible evaluation. The dataset is validated using existing GNSS spoofing detection approaches.

Preprint servers often host multiple versions of the same manuscript, but readers rarely learn what changed between them. In this thesis we will classify changes across preprint versions and distinguishing cosmetic edits (formatting, typography, ...) from substantive ones (altered results, revised claims, ...). Applied to roughly 5000 multi-version PsyArXiv preprints, the method quantifies how often version updates are substantive and how often such changes are disclosed in any author-provided note.