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@Inproceedings { 2022-rechenberg-cim,
   title = {Guiding Ship Navigators through the Heavy Seas of Cyberattacks},
   year = {2022},
   month = {10},
   keywords = {Maritime Cybersecurity, Intrusion Detection System, Integrated Bridge System, IEC 61162-450, NMEA 0183},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-rechenberg-guiding.pdf},
   web_url = {https://zenodo.org/record/7148794},
   publisher = {Zenodo},
   booktitle = {European Workshop on Maritime Systems Resilience and Security (MARESEC 2022)},
   event_place = {Bremerhaven, Germany},
   DOI = {10.5281/zenodo.7148794},
   reviewed = {1},
   author = {von Rechenberg, Merlin and R{\"o}{\ss}ler, Nina and Schmidt, Mari and Wolsing, Konrad and Motz, Florian and Bergmann, Michael and Padilla, Elmar and Bauer, Jan}
}

@Article { 2022-henze-tii-prada,
   title = {Complying with Data Handling Requirements in Cloud Storage Systems},
   journal = {IEEE Transactions on Cloud Computing},
   year = {2022},
   month = {9},
   volume = {10},
   number = {3},
   pages = {1661-1674},
   abstract = {In past years, cloud storage systems saw an enormous rise in usage. However, despite their popularity and importance as underlying infrastructure for more complex cloud services, today’s cloud storage systems do not account for compliance with regulatory, organizational, or contractual data handling requirements by design. Since legislation increasingly responds to rising data protection and privacy concerns, complying with data handling requirements becomes a crucial property for cloud storage systems. We present Prada , a practical approach to account for compliance with data handling requirements in key-value based cloud storage systems. To achieve this goal, Prada introduces a transparent data handling layer, which empowers clients to request specific data handling requirements and enables operators of cloud storage systems to comply with them. We implement Prada on top of the distributed database Cassandra and show in our evaluation that complying with data handling requirements in cloud storage systems is practical in real-world cloud deployments as used for microblogging, data sharing in the Internet of Things, and distributed email storage.},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-henze-tii-prada.pdf},
   misc2 = {Online},
   language = {en},
   ISSN = {2168-7161},
   DOI = {10.1109/TCC.2020.3000336},
   reviewed = {1},
   author = {Henze, Martin and Matzutt, Roman and Hiller, Jens and M{\"u}hmer, Erik and Ziegeldorf, Jan Henrik and van der Giet, Johannes and Wehrle, Klaus}
}

@Proceedings { 2022-wolsing-radarsec,
   title = {Network Attacks Against Marine Radar Systems: A Taxonomy, Simulation Environment, and Dataset},
   year = {2022},
   month = {9},
   tags = {rfc},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-wolsing-radar.pdf},
   publisher = {IEEE},
   event_place = {Edmonton, Canada},
   event_name = {47th IEEE Conference on Local Computer Networks (LCN)},
   event_date = {September 26-29, 2022},
   DOI = {10.1109/LCN53696.2022.9843801},
   reviewed = {1},
   author = {Wolsing, Konrad and Saillard, Antoine and Bauer, Jan and Wagner, Eric and van Sloun, Christian and Fink, Ina Berenice and Schmidt, Mari and Wehrle, Klaus and Henze, Martin}
}

@Inproceedings { 2022-wolsing-simple,
   title = {Can Industrial Intrusion Detection Be SIMPLE?},
   year = {2022},
   month = {9},
   volume = {978-3-031-17143-7},
   pages = {574--594},
   abstract = {Cyberattacks against industrial control systems pose a serious risk to the safety of humans and the environment. Industrial intrusion detection systems oppose this threat by continuously monitoring industrial processes and alerting any deviations from learned normal behavior. To this end, various streams of research rely on advanced and complex approaches, i.e., artificial neural networks, thus achieving allegedly high detection rates. However, as we show in an analysis of 70 approaches from related work, their inherent complexity comes with undesired properties. For example, they exhibit incomprehensible alarms and models only specialized personnel can understand, thus limiting their broad applicability in a heterogeneous industrial domain. Consequentially, we ask whether industrial intrusion detection indeed has to be complex or can be SIMPLE instead, i.e., Sufficient to detect most attacks, Independent of hyperparameters to dial-in, Meaningful in model and alerts, Portable to other industrial domains, Local to a part of the physical process, and computationally Efficient. To answer this question, we propose our design of four SIMPLE industrial intrusion detection systems, such as simple tests for the minima and maxima of process values or the rate at which process values change. Our evaluation of these SIMPLE approaches on four state-of-the-art industrial security datasets reveals that SIMPLE approaches can perform on par with existing complex approaches from related work while simultaneously being comprehensible and easily portable to other scenarios. Thus, it is indeed justified to raise the question of whether industrial intrusion detection needs to be inherently complex.},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-wolsing-simple.pdf},
   editor = {Atluri, Vijayalakshmi and Di Pietro, Roberto and Jensen, Christian D. and Meng, Weizhi},
   publisher = {Springer Nature Switzerland},
   booktitle = {Proceedings of the 27th European Symposium on Research in Computer Security (ESORICS '22), September 26-30, 2022, Copenhagen, Denmark},
   event_place = {Copenhagen, Denmark},
   event_name = {27th European Symposium on Research in Computer Security (ESORICS)},
   event_date = {September 26-30, 2022},
   DOI = {10.1007/978-3-031-17143-7_28},
   reviewed = {1},
   author = {Wolsing, Konrad and Thiemt, Lea and van Sloun, Christian and Wagner, Eric and Wehrle, Klaus and Henze, Martin}
}

@Article { 2022_brauner_iop,
   title = {A Computer Science Perspective on Digital Transformation in Production},
   journal = {ACM Transactions on Internet of Things},
   year = {2022},
   month = {5},
   day = {1},
   volume = {3},
   number = {2},
   abstract = {The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production, two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers: Smart human interfaces provide access to information that has been generated by model-integrated AI. Given the large variety of manufacturing data, new data modeling techniques should enable efficient management of Digital Shadows, which is supported by an interconnected infrastructure. Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality.},
   keywords = {Internet of Production; World Wide Lab; Digital Shadows; Industrial Internet of Things},
   tags = {internet-of-production},
   url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2022/2022-brauner-digital-transformation.pdf},
   publisher = {ACM},
   ISSN = {2691-1914},
   DOI = {10.1145/3502265},
   reviewed = {1},
   author = {Brauner, Philipp and Dalibor, Manuela and Jarke, Matthias and Kunze, Ike and Koren, Istv{\'a}n and Lakemeyer, Gerhard and Liebenberg, Martin and Michael, Judith and Pennekamp, Jan and Quix, Christoph and Rumpe, Bernhard and van der Aalst, Wil and Wehrle, Klaus and Wortmann, Andreas and Ziefle, Martina}
}