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Henrik Madsen, Gudmund Grov, Federico Mancini, Magnus Baksaas, Åvald Åslaugson Sommervoll. Exploring Reinforcement Learning for Incident Response in Autonomous Military Vehicles. In: Proceedings of DIGILIENCE 2024. arXiv preprint arXiv:2410.21407. https://doi.org/10.48550/arXiv.2410.21407
A. Jaber, M. Endregard, F. Mancini, G. Grov. Mission-Aware Cyber Incident Response Generation Using Reinforcement Learning. In: Proceedings of the NATO Science and Technology Organization Symposium (ICMCIS 2025), IST-209-RSY. Oeiras, Portugal, 13–14 May 2025. NATO STO, 2025.
G. Grov, J. Halvorsen, M. Eckhoff, B.J. Hansen, M. Eian, V. Mavroeidis, On the Use of Neurosymbolic AI for Defending Against Cyber Attacks. In: Besold, T.R., d’Avila Garcez, A., Jimenez-Ruiz, E., Confalonieri, R., Madhyastha, P., Wagner, B. (eds) Neural-Symbolic Learning and Reasoning. NeSy 2024. Lecture Notes in Computer Science, vol 14979. Springer, Cham. https://doi.org/10.1007/978-3-031-71167-1_7
A. Lemesle, A. Varasse, Z. Chihani, D. Tachet, AIMOS: Metamorphic Testing of AI - An Industrial Application. In: Guiochet, J., Tonetta, S., Schoitsch, E., Roy, M., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops. SAFECOMP 2023. Lecture Notes in Computer Science, vol 14182. Springer, Cham. https://doi.org/10.1007/978-3-031-40953-0_27
Max Landauer, Florian Skopik, and Markus Wurzenberger. A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-Based Anomaly Detection Techniques. Proc. ACM Softw. Eng. 1, FSE, Article 61 (July 2024), 22 pages. https://doi.org/10.1145/3660768
Patrick Himler, Max Landauer, Florian Skopik, and Markus Wurzenberger, Towards Detecting Anomalies in Log-Event Sequences with Deep Learning: Open Research Challenges. In Proceedings of the 2023 European Interdisciplinary Cybersecurity Conference (EICC '23). Association for Computing Machinery, New York, NY, USA, 71–77. https://doi.org/10.1145/3590777.3590789
Max Landauer, Sebastian Onder, Florian Skopik, Markus Wurzenberger, Deep learning for anomaly detection in log data: A survey, Machine Learning with Applications, Volume 12, 2023, 100470, ISSN 2666-8270,https://doi.org/10.1016/j.mlwa.2023.100470
Patrick Himler, Max Landauer, Florian Skopik, Markus Wurzenberger, Anomaly detection in log-event sequences: A federated deep learning approach and open challenges, Machine Learning with Applications, Volume 16, 2024, 100554, ISSN 2666-8270, https://doi.org/10.1016/j.mlwa.2024.100554
Zakaria Chihani, Trustworthy AI: Industry-Guided Tooling of the Methods. In Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering - Software Engineering for AI (CAIN '24). Association for Computing Machinery, New York, NY, USA, 245–246. https://doi.org/10.1145/3644815.3644970
Aws Jaber, Transforming Cybersecurity Dynamics: Enhanced Self-Play Reinforcement Learning in Intrusion Detection and Prevention System, 2024 IEEE International Systems Conference (SysCon), Montreal, QC, Canada, 2024, pp. 1-8, https://doi.org/10.1109/SysCon61195.2024.10553626
Markus Wurzenberger, Georg Höld, Max Landauer, Florian Skopik, Analysis of statistical properties of variables in log data for advanced anomaly detection in cyber security, Computers & Security, Volume 137, 2024, 103631, ISSN 0167-4048, https://doi.org/10.1016/j.cose.2023.103631
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