Trojan horse hunt in deep forecasting models: Insights from the European Space Agency competition

Computer Science > Machine Learning [Submitted on 20 Mar 2026] Trojan horse hunt in deep forecasting models: Insights from the European Space Agency competition Krzysztof Kotowski, Ramez Shendy, Jakub Nalepa, Agata Kaczmarek, Dawid Płudowski, Piotr Wilczyński, Artur Janicki, Przemysław Biecek, Ambros Marzetta, Atul Pande, Lalit Chandra Routhu, Swapnil Srivastava, Evridiki Ntagiou Forecasting plays a crucial role in modern safety-critical applications, such as space operations. However, the increasing use of deep forecasting models introduces a new security risk of trojan horse attacks, carried out by hiding a backdoor in the training data or directly in the model weights. Once implanted, the backdoor is activated by a specific trigger pattern at test time, causing the model to produce manipulated predictions. We focus on this issue in our \textit{Trojan Horse Hunt} data science competition, where more than 200 teams faced the task of identifying triggers hidden in deep forecasting models for spacecraft telemetry. We describe the novel task formulation, benchmark set, evaluation protocol, and best solutions from the competition. We further summarize key insights and research directions for effective identification of triggers in time series forecasting models. All materials are publicly available on the official competition webpage this https URL. Comments: 43 pages, 18 figures Subjects: Machine Learning (cs.LG); Cryptography and Security (cs.CR) Cite as: arXiv:2603.20108 [cs.LG]   (or arXiv:2603.20108v1 [cs.LG] for this version)   https://doi.org/10.48550/arXiv.2603.20108 Focus to learn more Submission history From: Krzysztof Kotowski PhD [view email] [v1] Fri, 20 Mar 2026 16:32:47 UTC (3,299 KB) Access Paper: HTML (experimental) view license Current browse context: cs.LG < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)