@article{WilbringEnningPfaffetal.2020,
  author    = {Wilbring, Daniela and Enning, Manfred and Pfaff, Raphael and Schmidt, Bernd},
  title     = {Neue Perspektiven f{\"u}r die Bahn in der Produktions- und Distributionslogistik durch Prozessautomation},
  series = {ETR - Eisenbahntechnische Rundschau},
  volume    = {69},
  journal   = {ETR - Eisenbahntechnische Rundschau},
  number    = {3},
  issn      = {0013-2845},
  pages     = {15 -- 19},
  year      = {2020},
  language  = {de}
}
@inproceedings{DinghoferHartung2020,
  author    = {Dinghofer, Kai and Hartung, Frank},
  title     = {Analysis of Criteria for the Selection of Machine Learning Frameworks},
  series = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  booktitle = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1109/ICNC47757.2020.9049650},
  pages     = {373 -- 377},
  year      = {2020},
  abstract  = {With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.},
  language  = {en}
}
@inproceedings{KreyerMuellerEsch2020,
  author    = {Kreyer, J{\"o}rg and M{\"u}ller, Marvin and Esch, Thomas},
  title     = {A Map-Based Model for the Determination of Fuel Consumption for Internal Combustion Engines as a Function of Flight Altitude},
  publisher = {DGLR},
  address   = {Bonn},
  doi       = {10.25967/490162},
  pages     = {13 Seiten},
  year      = {2020},
  abstract  = {In addition to very high safety and reliability requirements, the design of internal combustion engines (ICE) in aviation focuses on economic efficiency. The objective must be to design the aircraft powertrain optimized for a specific flight mission with respect to fuel consumption and specific engine power. Against this background, expert tools provide valuable decision-making assistance for the customer. In this paper, a mathematical calculation model for the fuel consumption of aircraft ICE is presented. This model enables the derivation of fuel consumption maps for different engine configurations. Depending on the flight conditions and based on these maps, the current and the integrated fuel consumption for freely definable flight emissions is calculated. For that purpose, an interpolation method is used, that has been optimized for accuracy and calculation time. The mission boundary conditions flight altitude and power requirement of the ICE form the basis for this calculation. The mathematical fuel consumption model is embedded in a parent program. This parent program presents the simulated fuel consumption by means of an example flight mission for a representative airplane. The focus of the work is therefore on reproducing exact consumption data for flight operations. By use of the empirical approaches according to Gagg-Farrar [1] the power and fuel consumption as a function of the flight altitude are determined. To substantiate this approaches, a 1-D ICE model based on the multi-physical simulation tool GT-Suite® has been created. This 1-D engine model offers the possibility to analyze the filling and gas change processes, the internal combustion as well as heat and friction losses for an ICE under altitude environmental conditions. Performance measurements on a dynamometer at sea level for a naturally aspirated ICE with a displacement of 1211 ccm used in an aviation aircraft has been done to validate the 1-D ICE model. To check the plausibility of the empirical approaches with respect to the fuel consumption and performance adjustment for the flight altitude an analysis of the ICE efficiency chain of the 1-D engine model is done. In addition, a comparison of literature and manufacturer data with the simulation results is presented.},
  language  = {en}
}
@inproceedings{FingerdeVriesVosetal.2020,
  author    = {Finger, Felix and de Vries, Reynard and Vos, Roelof and Braun, Carsten and Bil, Cees},
  title     = {A comparison of hybrid-electric aircraft sizing methods},
  series = {AIAA Scitech 2020 Forum},
  booktitle = {AIAA Scitech 2020 Forum},
  doi       = {10.2514/6.2020-1006},
  pages     = {31 Seiten},
  year      = {2020},
  abstract  = {The number of case studies focusing on hybrid-electric aircraft is steadily increasing, since these configurations are thought to lead to lower operating costs and environmental impact than traditional aircraft. However, due to the lack of reference data of actual hybrid-electric aircraft, in most cases, the design tools and results are difficult to validate. In this paper, two independently developed approaches for hybrid-electric conceptual aircraft design are compared. An existing 19-seat commuter aircraft is selected as the conventional baseline, and both design tools are used to size that aircraft. The aircraft is then re-sized under consideration of hybrid-electric propulsion technology. This is performed for parallel, serial, and fully-electric powertrain architectures. Finally, sensitivity studies are conducted to assess the validity of the basic assumptions and approaches regarding the design of hybrid-electric aircraft. Both methods are found to predict the maximum take-off mass (MTOM) of the reference aircraft with less than 4\% error. The MTOM and payload-range energy efficiency of various (hybrid-) electric configurations are predicted with a maximum difference of approximately 2\% and 5\%, respectively. The results of this study confirm a correct formulation and implementation of the two design methods, and the data obtained can be used by researchers to benchmark and validate their design tools.},
  language  = {en}
}
@article{KhayyamJamaliBabHadiasharetal.2020,
  author    = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalil, Mahdi and Naebe, Minoo},
  title     = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modelling with Application in Industry 4.0},
  series = {IEEE Access},
  journal   = {IEEE Access},
  publisher = {IEEE},
  address   = {New York, NY},
  isbn      = {2169-3536},
  doi       = {10.1109/ACCESS.2020.2999898},
  pages     = {1 -- 12},
  year      = {2020},
  abstract  = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.},
  language  = {en}
}
@inproceedings{HauggKreyerKemperetal.2020,
  author    = {Haugg, Albert Thomas and Kreyer, J{\"o}rg and Kemper, Hans and Hatesuer, Katerina and Esch, Thomas},
  title     = {Heat exchanger for ORC. adaptability and optimisation potentials},
  series = {IIR International Rankine 2020 Conference},
  booktitle = {IIR International Rankine 2020 Conference},
  doi       = {10.18462/iir.rankine.2020.1224},
  pages     = {10 Seiten},
  year      = {2020},
  abstract  = {The recovery of waste heat requires heat exchangers to extract it from a liquid or gaseous medium into another working medium, a refrigerant. In Organic Rankine Cycles (ORC) on Combustion Engines there are two major heat sources, the exhaust gas and the water/glycol fluid from the engine's cooling circuit. A heat exchanger design must be adapted to the different requirements and conditions resulting from the heat sources, fluids, system configurations, geometric restrictions, and etcetera. The Stacked Shell Cooler (SSC) is a new and very specific design of a plate heat exchanger, created by AKG, which allows with a maximum degree of freedom the optimization of heat exchange rate and the reduction of the related pressure drop. This optimization in heat exchanger design for ORC systems is even more important, because it reduces the energy consumption of the system and therefore maximizes the increase in overall efficiency of the engine.},
  language  = {en}
}
@inproceedings{NikolovskiRekeElsenetal.2021,
  author    = {Nikolovski, Gjorgji and Reke, Michael and Elsen, Ingo and Schiffer, Stefan},
  title     = {Machine learning based 3D object detection for navigation in unstructured environments},
  series = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)},
  booktitle = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)},
  publisher = {IEEE},
  isbn      = {978-1-6654-7921-9},
  doi       = {10.1109/IVWorkshops54471.2021.9669218},
  pages     = {236 -- 242},
  year      = {2021},
  abstract  = {In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.},
  language  = {en}
}
@incollection{HebelHerrmannRitzetal.2022,
  author    = {Hebel, Christoph and Herrmann, Ulf and Ritz, Thomas and R{\"o}th, Thilo and Anthrakidis, Anette and B{\"o}ker, J{\"o}rg and Franzke, Till and Grodzki, Thomas and Merkens, Torsten and Sch{\"o}ttler, Mirjam},
  title     = {FlexSHARE - Methodisches Framework zur innovativen Gestaltung der urbanen Mobilit{\"a}t durch Sharing- Angebote},
  series = {Transforming Mobility - What Next?},
  booktitle = {Transforming Mobility - What Next?},
  publisher = {Springer Gabler},
  address   = {Wiesbaden},
  isbn      = {978-3-658-36429-8},
  doi       = {10.1007/978-3-658-36430-4_10},
  pages     = {153 -- 169},
  year      = {2022},
  abstract  = {Das Ziel des INTERREG-Projektes „SHAREuregio" (FKZ: 34.EFRE-0300134) ist es, grenz{\"u}berschreitende Mobilit{\"a}t in der Euregio Rhein-Maas-Nord zu erm{\"o}glichen und zu f{\"o}rdern. Dazu soll ein elektromobiles Car- und Bikesharing- System entwickelt und in der Stadt M{\"o}nchengladbach, im Kreis Viersen sowie in den Gemeinden Roermond und Venlo (beide NL) zusammen mit den Partnern Wirtschaftsf{\"o}rderung M{\"o}nchengladbach, Wirtschaftsf{\"o}rderung f{\"u}r den Kreis Viersen, NEW AG, Goodmoovs (NL), Greenflux (NL) und der FH Aachen implementiert werden. Zun{\"a}chst richtet sich das Angebot, bestehend aus 40 Elektroautos und 40 Elektrofahrr{\"a}dern, an Unternehmen und wird nach einer Erprobungsphase, mit einer gr{\"o}ßeren Anzahl an Fahrzeugen, auch f{\"u}r Privatpersonen verf{\"u}gbar gemacht werden. Die Fahrzeuge stehen bei den jeweiligen Anwendungspartnern in Deutschland und den Niederlanden. Im Rahmen dieses Projektes hat die FH Aachen „FlexSHARE" entwickelt - ein methodisches Framework zur innovativen Gestaltung urbaner Sharing- Angebote. Das Framework erm{\"o}glicht es, anhand von messbaren Kenngr{\"o}ßen, bedarfsgerechte und auf die Region abgestimmte Sharing-Systeme zu entwickeln.},
  language  = {de}
}
@inproceedings{FiedlerGottschlichMuellerMelcher2021,
  author    = {Fiedler, Gerda and Gottschlich-M{\"u}ller, Birgit and Melcher, Karin},
  title     = {Online-Pr{\"u}fungen mit STACK Aufgaben},
  series = {Tagungsband ASIM Workshop STS/GMMS/EDU 2021},
  booktitle = {Tagungsband ASIM Workshop STS/GMMS/EDU 2021},
  editor    = {Liu-Henke, Xiaobo and Durak, Umut},
  publisher = {ARGESIM Verlag},
  address   = {Wien},
  isbn      = {978-3-901608-69-8},
  doi       = {10.11128/arep.45},
  pages     = {173 -- 178},
  year      = {2021},
  abstract  = {Wir stellen hier exemplarisch STACK Aufgaben vor, die frei von der Problematik sind, welche sich durch diverse Kommunikationswege und (webbasierte) Computer Algebra Systeme (CAS) ergibt. Daher sind sie insbesondere f{\"u}r eine Open-Book Online Pr{\"u}fung geeignet, da eine faire Pr{\"u}fungssituation gew{\"a}hrleistet werden kann.},
  language  = {de}
}
@article{HahnHebelManz2022,
  author    = {Hahn, Geogr W. and Hebel, Christoph and Manz, W.},
  title     = {Die neuen Empfehlungen f{\"u}r Verkehrsnachfragemodellierung im Personenverkehr},
  series = {Straßenverkehrstechnik},
  volume    = {66},
  journal   = {Straßenverkehrstechnik},
  number    = {10},
  publisher = {Kirschbaum Verlag GmbH},
  address   = {Bonn},
  issn      = {0039-2219},
  doi       = {10.53184/SVT10-2022-1},
  pages     = {721 -- 726},
  year      = {2022},
  abstract  = {Die neu erschienenen „Empfehlungen zum Einsatz von Verkehrsnachfragemodellen f{\"u}r den Personenverkehr" liefern erstmals als Empfehlungspapier der Forschungsgesellschaft f{\"u}r Straßen- und Verkehrswesen einen umfassenden {\"U}berblick zu den verschiedenen Aspekten der Modellierung und geben dem Fachplaner konkrete Hilfestellung f{\"u}r die Konzeption von Nachfragemodellen. Das Empfehlungspapier zielt unter anderem darauf ab, die Erwartungen und das Anspruchsniveau in Hinblick auf Sachgerechtigkeit der Modelle, die erzielbare Modellqualit{\"a}t und den Detaillierungsgrad der Modellaussagen zu harmonisieren.},
  language  = {de}
}
@article{EmigHebelSchwark2022,
  author    = {Emig, J. and Hebel, Christoph and Schwark, A.},
  title     = {Einsatzbereiche f{\"u}r Verkehrsnachfragemodelle},
  series = {Straßenverkehrstechnik},
  volume    = {66},
  journal   = {Straßenverkehrstechnik},
  number    = {10},
  publisher = {Kirschbaum Verlag GmbH},
  address   = {Bonn},
  issn      = {0039-2219},
  doi       = {10.53184/SVT10-2022-2},
  pages     = {727 -- 736},
  year      = {2022},
  abstract  = {In der Praxis bestehen vielf{\"a}ltige Einsatzbereiche f{\"u}r Verkehrsnachfragemodelle. Mit ihnen k{\"o}nnen Kenngr{\"o}ßen des Verkehrsangebots und der Verkehrsnachfrage f{\"u}r den heutigen Zustand wie auch f{\"u}r zuk{\"u}nftige Zust{\"a}nde bereitgestellt werden, um so die Grundlagen f{\"u}r verkehrsplanerische Entscheidungen zu liefern. Die neuen „Empfehlungen zum Einsatz von Verkehrsnachfragemodellen f{\"u}r den Personenverkehr" (EVNM-PV) (FGSV 2022) veranschaulichen anhand von typischen Planungsaufgaben, welche differenzierten Anforderungen daraus f{\"u}r die Modellkonzeption und -erstellung resultieren. Vor dem Hintergrund der konkreten Aufgabenstellung sowie deren spezifischer planerischer Anforderungen bildet die abzuleitende Modellspezifikation die verabredete Grundlage zwischen Auftraggeber und Modellersteller f{\"u}r die konkrete inhaltliche, fachliche Ausgestaltung des Verkehrsmodells.},
  language  = {de}
}
@article{HoevelerBauknechtWolfetal.2020,
  author    = {Hoeveler, B. and Bauknecht, Andr{\´e} and Wolf, C. Christian and Janser, Frank},
  title     = {Wind-Tunnel Study of a Wing-Embedded Lifting Fan Remaining Open in Cruise Flight},
  series = {Journal of Aircraft},
  volume    = {57},
  journal   = {Journal of Aircraft},
  number    = {4},
  publisher = {AIAA},
  address   = {Reston, Va.},
  issn      = {1533-3868},
  doi       = {10.2514/1.C035422},
  year      = {2020},
  abstract  = {It is investigated whether a nonrotating lifting fan remaining uncovered during cruise flight, as opposed to being covered by a shutter system, can be realized with limited additional drag and loss of lift during cruise flight. A wind-tunnel study of a wing-embedded lifting fan has been conducted at the Side Wind Test Facility G{\"o}ttingen of DLR, German Aerospace Center in G{\"o}ttingen using force, pressure, and stereoscopic particle image velocimetry techniques. The study showed that a step on the lower side of the wing in front of the lifting fan duct increases the lift-to-drag ratio of the whole model by up to 25\% for all positive angles of attack. Different sizes and inclinations of the step had limited influence on the surface pressure distribution. The data indicate that these parameters can be optimized to maximize the lift-to-drag ratio. A doubling of the curvature radius of the lifting fan duct inlet lip on the upper side of the wing affected the lift-to-drag ratio by less than 1\%. The lifting fan duct inlet curvature can therefore be optimized to maximize the vertical fan thrust of the rotating lifting fan during hovering without affecting the cruise flight performance with a nonrotating fan.},
  language  = {en}
}
@article{KhayyamJamaliBabHadiasharetal.2020,
  author    = {Khayyam, Hamid and Jamali, Ali and Bab-Hadiashar, Alireza and Esch, Thomas and Ramakrishna, Seeram and Jalili, Mahdi and Naebe, Minoo},
  title     = {A Novel Hybrid Machine Learning Algorithm for Limited and Big Data Modeling with Application in Industry 4.0},
  series = {IEEE Access},
  volume    = {8},
  journal   = {IEEE Access},
  number    = {Art. 9108222},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {2169-3536},
  doi       = {10.1109/ACCESS.2020.2999898},
  pages     = {111381 -- 111393},
  year      = {2020},
  abstract  = {To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.},
  language  = {en}
}
@article{NeuJanserKhatibietal.2017,
  author    = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.},
  title     = {Fully Automated Operational Modal Analysis using multi-stage clustering},
  series = {Mechanical Systems and Signal Processing},
  volume    = {Vol. 84, Part A},
  journal   = {Mechanical Systems and Signal Processing},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0888-3270},
  doi       = {10.1016/j.ymssp.2016.07.031},
  pages     = {308 -- 323},
  year      = {2017},
  language  = {en}
}
@article{NeuJanserKhatibietal.2016,
  author    = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.},
  title     = {Automated modal parameter-based anomaly detection under varying wind excitation},
  series = {Structural Health Monitoring},
  volume    = {15},
  journal   = {Structural Health Monitoring},
  number    = {6},
  publisher = {Sage},
  address   = {London},
  issn      = {1475-9217},
  doi       = {10.1177/1475921716665803},
  pages     = {1 -- 20},
  year      = {2016},
  abstract  = {Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.},
  language  = {en}
}
@article{RuppSchulzeKuperjans2018,
  author    = {Rupp, Matthias and Schulze, Sven and Kuperjans, Isabel},
  title     = {Comparative life cycle analysis of conventional and hybrid heavy-duty trucks},
  series = {World electric vehicle journal},
  volume    = {9},
  journal   = {World electric vehicle journal},
  number    = {2},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2032-6653},
  doi       = {10.3390/wevj9020033},
  pages     = {Article No. 33},
  year      = {2018},
  abstract  = {Heavy-duty trucks are one of the main contributors to greenhouse gas emissions in German traffic. Drivetrain electrification is an option to reduce tailpipe emissions by increasing energy conversion efficiency. To evaluate the vehicle's environmental impacts, it is necessary to consider the entire life cycle. In addition to the daily use, it is also necessary to include the impact of production and disposal. This study presents the comparative life cycle analysis of a parallel hybrid and a conventional heavy-duty truck in long-haul operation. Assuming a uniform vehicle glider, only the differing parts of both drivetrains are taken into account to calculate the environmental burdens of the production. The use phase is modeled by a backward simulation in MATLAB/Simulink considering a characteristic driving cycle. A break-even analysis is conducted to show at what mileage the larger CO2eq emissions due to the production of the electric drivetrain are compensated. The effect of parameter variation on the break-even mileage is investigated by a sensitivity analysis. The results of this analysis show the difference in CO2eq/t km is negative, indicating that the hybrid vehicle releases 4.34 g CO2eq/t km over a lifetime fewer emissions compared to the diesel truck. The break-even analysis also emphasizes the advantages of the electrified drivetrain, compensating the larger emissions generated during production after already a distance of 15,800 km (approx. 1.5 months of operation time). The intersection coordinates, distance, and CO2eq, strongly depend on fuel, emissions for battery production and the driving profile, which lead to nearly all parameter variations showing an increase in break-even distance.},
  language  = {en}
}
@incollection{SchubaHoefken2022,
  author    = {Schuba, Marko and H{\"o}fken, Hans-Wilhelm},
  title     = {Cybersicherheit in Produktion, Automotive und intelligenten Geb{\"a}uden},
  series = {IT-Sicherheit - Technologien und Best Practices f{\"u}r die Umsetzung im Unternehmen},
  booktitle = {IT-Sicherheit - Technologien und Best Practices f{\"u}r die Umsetzung im Unternehmen},
  publisher = {Carl Hanser Verlag},
  address   = {M{\"u}nchen},
  isbn      = {978-3-446-47223-5},
  doi       = {10.3139/9783446473478.012},
  pages     = {193 -- 218},
  year      = {2022},
  language  = {de}
}
@incollection{EnglaenderKaminskiSchuba2022,
  author    = {Engl{\"a}nder, Jacques and Kaminski, Lars and Schuba, Marko},
  title     = {Informationssicherheitsmanagement},
  series = {Digitalisierungs- und Informationsmanagement},
  booktitle = {Digitalisierungs- und Informationsmanagement},
  publisher = {Springer Vieweg},
  address   = {Berlin},
  isbn      = {978-3-662-63757-9},
  doi       = {10.1007/978-3-662-63758-6_15},
  pages     = {373 -- 398},
  year      = {2022},
  abstract  = {Daten und Informationen sind die wichtigsten Ressourcen vieler Unternehmen und m{\"u}ssen daher entsprechend gesch{\"u}tzt werden. Getrieben durch die erh{\"o}hte Vernetzung von Informationstechnologie, die h{\"o}here Offenheit infolge datengetriebener Dienstleistungen und eine starke Zunahme an Datenquellen, r{\"u}cken die Gefahren von Informationsdiebstahl, -manipulation und -verlust in den Fokus von produzierenden Unternehmen. Auf dem Weg zum lern- und wandlungsf{\"a}higen Unternehmen kann dies zu einem großen Hindernis werden, da einerseits zu hohe Sicherheitsanforderungen neue Entwicklungen beschr{\"a}nken, andererseits wegen des Mangels an ausreichenden Informationssicherheitskonzepten Unternehmen weniger Innovationen wagen. Deshalb bedarf es individuell angepasster Konzepte f{\"u}r die Bereiche IT-Security, IT-Safety und Datenschutz f{\"u}r vernetzte Produkte, Produktion und Arbeitspl{\"a}tze. Bei der Entwicklung und Durchsetzung dieser Konzepte steht der Faktor Mensch im Zentrum aller {\"U}berlegungen. In diesem Kapitel wird dargestellt, wie der Faktor Mensch bei der Erstellung von Informationssicherheitskonzepten in verschiedenen Phasen zu beachten ist. Beginnend mit der Integration von Informationssystemen und damit verbundenen Sicherheitsmaßnahmen, {\"u}ber die Administration, bis hin zur Anwendung durch den Endnutzer, werden Methoden beschrieben, die den Menschen, verbunden mit seinem Mehrwert wie auch den Risiken, einschließen. Dabei werden sowohl Grundlagen aufgezeigt als auch Konzepte vorgestellt, mit denen Entscheider in der Unternehmens-IT Leitlinien f{\"u}r die Informationssicherheit festlegen k{\"o}nnen.},
  language  = {de}
}
@inproceedings{SchubaHoefkenLinzbach2022,
  author    = {Schuba, Marko and H{\"o}fken, Hans-Wilhelm and Linzbach, Sophie},
  title     = {An ICS Honeynet for Detecting and Analyzing Cyberattacks in Industrial Plants},
  series = {2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)},
  booktitle = {2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)},
  publisher = {IEEE},
  isbn      = {978-1-6654-4231-2},
  doi       = {10.1109/ICECET52533.2021.9698746},
  pages     = {6 Seiten},
  year      = {2022},
  abstract  = {Cybersecurity of Industrial Control Systems (ICS) is an important issue, as ICS incidents may have a direct impact on safety of people or the environment. At the same time the awareness and knowledge about cybersecurity, particularly in the context of ICS, is alarmingly low. Industrial honeypots offer a cheap and easy to implement way to raise cybersecurity awareness and to educate ICS staff about typical attack patterns. When integrated in a productive network, industrial honeypots may not only reveal attackers early but may also distract them from the actual important systems of the network. Implementing multiple honeypots as a honeynet, the systems can be used to emulate or simulate a whole Industrial Control System. This paper describes a network of honeypots emulating HTTP, SNMP, S7communication and the Modbus protocol using Conpot, IMUNES and SNAP7. The nodes mimic SIMATIC S7 programmable logic controllers (PLCs) which are widely used across the globe. The deployed honeypots' features will be compared with the features of real SIMATIC S7 PLCs. Furthermore, the honeynet has been made publicly available for ten days and occurring cyberattacks have been analyzed},
  language  = {en}
}
@inproceedings{ChristianMontagSchubaetal.2018,
  author    = {Christian, Esser and Montag, Tim and Schuba, Marko and Allhof, Manuel},
  title     = {Future critical infrastructure and security - cyberattacks on charging stations},
  series = {31st International Electric Vehicle Symposium \& Exhibition and International Electric Vehicle Technology Conference (EVS31 \& EVTeC 2018)},
  booktitle = {31st International Electric Vehicle Symposium \& Exhibition and International Electric Vehicle Technology Conference (EVS31 \& EVTeC 2018)},
  publisher = {Society of Automotive Engineers of Japan (JSAE)},
  address   = {Tokyo},
  isbn      = {978-1-5108-9157-9},
  pages     = {665 -- 671},
  year      = {2018},
  language  = {en}
}