The MAGIC project (2025–2028) is actively producing research results. This page will be updated as publications, deliverables, and datasets are released.
Project Deliverables
| Deliverable | Title | WP | Status |
|---|---|---|---|
| D2.1 | Report on Industrial Needs and Use Cases | WP2 | Planned (Dec 2026) |
| D2.2 | State-of-the-Art Report | WP2 | Planned (Dec 2026) |
| D3.1 | ADF-Supported Architecture with Requirements and Guidelines | WP3 | Planned (Dec 2027) |
| D4.1 | Forensic Soundness and Data Collection for ADF | WP4 | Planned (Dec 2027) |
| D4.2 | Enhanced IDS Methodologies for ADF | WP4 | Planned (Dec 2028) |
| D5.1 | Management of Digital Evidence | WP5 | Planned (Dec 2027) |
| D5.2 | ADF and IDS Maintainability and Online Adaptation | WP5 | Planned (Dec 2028) |
| D5.3 | Evaluation of Resilient ADF Mechanisms | WP5 | Planned (Dec 2028) |
Publications & Reports
@InProceedings{10.1007/978-3-032-00627-1_13,
author="Strandberg, Kim
and Eldefrawy, Mohamed",
editor="Dalla Preda, Mila
and Schrittwieser, Sebastian
and Naessens, Vincent
and De Sutter, Bjorn",
title="Advances in Automotive Digital Forensics: Recent Trends and Future Directions",
booktitle="Availability, Reliability and Security",
year="2025",
publisher="Springer Nature Switzerland",
address="Cham",
pages="252--274",
abstract="The automotive industry is increasingly facing growing cybersecurity challenges as vehicles become more connected and autonomous. Modern cars equipped with sophisticated electronic systems are becoming more susceptible to cyber threats. Enhancing detection and forensic capabilities within automotive systems is essential to mitigate these risks. This work builds on and extends a previous systematic literature review of automotive digital forensics, covering 2006 to early 2021. However, recent advances in the field have introduced new challenges and opportunities, particularly in light of an evolving, dynamic threat landscape and growing vehicle complexity. These developments have driven numerous advances, particularly in artificial intelligence, machine learning, and blockchain technologies. In response, we review the latest state-of-the-art developments from 2021 to 2025, addressing critical challenges and technical solutions to provide a comprehensive understanding of the evolving landscape and its implications for both researchers and practitioners. By categorizing and comparing these advancements with prior research, we highlight key trends and innovations, analyze security concerns, and ultimately offer valuable insights into future research directions and emerging trends.",
isbn="978-3-032-00627-1",
doi="10.1007/978-3-032-00627-1_13"
}
@INPROCEEDINGS{11467947,
author={Mowla, Nishat I and Rosell, Joakim and Abedin, Sarder Fakhrul},
booktitle={2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA)},
title={Benchmarking Explainable Machine Learning Models for Automotive Intrusion Detection},
year={2026},
volume={},
number={},
pages={1-6},
keywords={Payloads;Feeds;Central Processing Unit;Internet of Things;Radio frequency;Communication systems;Protocols;Communications technology;Internet;Internet of Vehicles;Vehicular Network;Intrusion Detection System;XAI;Machine Learning;Network Attacks},
doi={10.1109/ACDSA67686.2026.11467947}
}
@ARTICLE{11523163,
author={Mowla, Nishat I. and Thar, Kyi and Abedin, Sarder Fakhrul and Mahmood, Aamir and Han, Zhu and Gidlund, Mikael and Fahria, Kabir and Giapantzis, Konstantinos and Lalas, Antonios and Rosell, Joakim and Moghadam, Mahshid Helali},
journal={IEEE Transactions on Intelligent Transportation Systems},
title={ACHILLES: A Machine Learning Framework for Explainable and Generalized Automotive Intrusion Detection System},
year={2026},
volume={},
number={},
pages={1-16},
keywords={Modeling;Automotive engineering;Metalearning;Training;Controller area networks;Vehicles;Timing;Radio frequency;Testing;Machine learning;In-vehicle networks (IVNs);automotive intrusion detection;generalizability;explainable AI (XAI)},
doi={10.1109/TITS.2026.3688299}
}