Trojan Horse Hunt in deep forecasting models: Insights from the European Space Agency competition
Authors:
- Krzysztof KotowskiKKKrzysztof Kotowski
- Ramez ShendyRSRamez Shendy
- Jakub NalepaJakub Nalepa
- Agata KaczmarekAKAgata Kaczmarek
- Dawid PłudowskiDPDawid Płudowski
- Piotr WilczyńskiPWPiotr Wilczyński
- Artur JanickiAJArtur Janicki
- Przemysław BiecekPBPrzemysław Biecek
- Ambros MarzettaAMAmbros Marzetta
- Atul PandeAPAtul Pande
- Lalit Chandra RouthuLRLalit Chandra Routhu
- Swapnil SrivastavaSSSwapnil Srivastava
- 2 November 2026
- journal article
- Published by Elsevier in International Journal of Forecasting
Abstract
No abstract availableFunding Information
- European Space Agency
- Silesian University of Technology
- Fundacja na rzecz Nauki Polskiej
This publication has 11 references indexed in Scilit:
- Anomaly detection for space information networks: A survey of challenges, techniques, and future directionsComputers & Security, 2024
- Artificial Intelligence-Based Short-Term Satellite Health Forecasting2024
- NHITS: Neural Hierarchical Interpolation for Time Series ForecastingProceedings of the AAAI Conference on Artificial Intelligence, 2023
- DLP: towards active defense against backdoor attacks with decoupled learning processCybersecurity, 2023
- Backdoor Learning: A SurveyIEEE Transactions on Neural Networks and Learning Systems, 2022
- Machine-learning ready data on the thermal power consumption of the Mars Express SpacecraftScientific Data, 2022
- Spacecraft collision avoidance challenge: Design and results of a machine learning competitionAstrodynamics, 2021
- A survey on adversarial attacks and defencesCAAI Transactions on Intelligence Technology, 2021
- Defense against neural trojan attacks: A surveyNeurocomputing, 2021
- Smoothing and Differentiation of Data by Simplified Least Squares Procedures.Analytical Chemistry, 1964