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@Article { 2023_lamberts_metrics-sok,
   title = {SoK: Evaluations in Industrial Intrusion Detection Research},
   journal = {Journal of Systems Research},
   year = {2023},
   month = {10},
   day = {31},
   volume = {3},
   number = {1},
   abstract = {Industrial systems are increasingly threatened by cyberattacks with potentially disastrous consequences. To counter such attacks, industrial intrusion detection systems strive to timely uncover even the most sophisticated breaches. Due to its criticality for society, this fast-growing field attracts researchers from diverse backgrounds, resulting in 130 new detection approaches in 2021 alone. This huge momentum facilitates the exploration of diverse promising paths but likewise risks fragmenting the research landscape and burying promising progress. Consequently, it needs sound and comprehensible evaluations to mitigate this risk and catalyze efforts into sustainable scientific progress with real-world applicability. In this paper, we therefore systematically analyze the evaluation methodologies of this field to understand the current state of industrial intrusion detection research. Our analysis of 609 publications shows that the rapid growth of this research field has positive and negative consequences. While we observe an increased use of public datasets, publications still only evaluate 1.3 datasets on average, and frequently used benchmarking metrics are ambiguous. At the same time, the adoption of newly developed benchmarking metrics sees little advancement. Finally, our systematic analysis enables us to provide actionable recommendations for all actors involved and thus bring the entire research field forward.},
   tags = {internet-of-production, rfc},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-lamberts-metrics-sok.pdf},
   publisher = {eScholarship Publishing},
   ISSN = {2770-5501},
   DOI = {10.5070/SR33162445},
   reviewed = {1},
   author = {Lamberts, Olav and Wolsing, Konrad and Wagner, Eric and Pennekamp, Jan and Bauer, Jan and Wehrle, Klaus and Henze, Martin}
}

@Inproceedings { 2020-henze-ccs-cybersecurity,
   title = {Poster: Cybersecurity Research and Training for Power Distribution Grids -- A Blueprint},
   year = {2020},
   month = {11},
   day = {9},
   abstract = {Mitigating cybersecurity threats in power distribution grids requires a testbed for cybersecurity, e.g., to evaluate the (physical) impact of cyberattacks, generate datasets, test and validate security approaches, as well as train technical personnel. In this paper, we present a blueprint for such a testbed that relies on network emulation and power flow computation to couple real network applications with a simulated power grid. We discuss the benefits of our approach alongside preliminary results and various use cases for cybersecurity research and training for power distribution grids.},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-henze-ccs-cybersecurity.pdf},
   publisher = {ACM},
   address = {New York, NY, USA},
   booktitle = {Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security (CCS ’20), November 9–13, 2020, Virtual Event, USA.},
   event_place = {Virtual Event, USA},
   event_date = {November 9-13, 2020},
   DOI = {10.1145/3372297.3420016},
   reviewed = {1},
   author = {Henze, Martin and Bader, Lennart and Filter, Julian and Lamberts, Olav and Ofner, Simon and van der Velde, Dennis}
}