Adversarial Machine Learning: Modeling and Simulation Results

Farhana Uddin, Lukas Kowalski, Anika Mondal

Open Access Journal of Engineering Applications · doi:10.55555/oajea.2025.4901.005

1. Introduction

The scale-up of railway track systems from pilot to commercial deployment raises new questions about adversarial machine learning. Full-scale trials were conducted in railway track systems to assess the practicality of the approach. Removal efficiency exceeded 62% under the optimized operating conditions. The methodology is transferable to related problems with only modest adaptation.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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