@inproceedings{GaldiHartungDugelay2017, author = {Galdi, Chiara and Hartung, Frank and Dugelay, Jean-Luc}, title = {Videos versus still images: Asymmetric sensor pattern noise comparison on mobile phones}, series = {Electronic Imaging}, booktitle = {Electronic Imaging}, publisher = {Society for Imaging Science and Technology}, address = {Springfield, Virginia}, issn = {2470-1173}, doi = {10.2352/ISSN.2470-1173.2017.7.MWSF-331}, pages = {100 -- 103}, year = {2017}, abstract = {Nowadays, the most employed devices for recoding videos or capturing images are undoubtedly the smartphones. Our work investigates the application of source camera identification on mobile phones. We present a dataset entirely collected by mobile phones. The dataset contains both still images and videos collected by 67 different smartphones. Part of the images consists in photos of uniform backgrounds, especially collected for the computation of the RSPN. Identifying the source camera given a video is particularly challenging due to the strong video compression. The experiments reported in this paper, show the large variation in performance when testing an highly accurate technique on still images and videos.}, 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} } @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} } @techreport{ThomaLaarmannMerkensetal.2020, author = {Thoma, Andreas and Laarmann, Lukas and Merkens, Torsten and Franzke, Till and M{\"o}hren, Felix and Buttermann, Lilly and van der Weem, Dirk and Fischer, Maximilian and Misch, Philipp and B{\"o}hme, Mirijam and R{\"o}th, Thilo and Hebel, Christoph and Ritz, Thomas and Franke, Marina and Braun, Carsten}, title = {Entwicklung eines intermodalen Mobilit{\"a}tskonzeptes f{\"u}r die Pilotregion NRW/Rhein-Maas Euregio und Schaffung voller Kundenakzeptanz durch Transfer von Standards aus dem PKW-Bereich auf ein Flugtaxi : Schlussbericht : Projektakronym: SkyCab (Kategorie B) : Laufzeit in Monaten: 6 : Hauptthema: Kategorie B: Innovative Ideen mit Bezug zu UAS/Flugtaxis}, publisher = {FH Aachen}, address = {Aachen}, pages = {97 Seiten}, year = {2020}, language = {de} } @article{SerrorHackHenzeetal.2021, author = {Serror, Martin and Hack, Sacha and Henze, Martin and Schuba, Marko and Wehrle, Klaus}, title = {Challenges and Opportunities in Securing the Industrial Internet of Things}, series = {IEEE Transactions on Industrial Informatics}, volume = {17}, journal = {IEEE Transactions on Industrial Informatics}, number = {5}, publisher = {IEEE}, address = {New York}, issn = {1941-0050}, doi = {10.1109/TII.2020.3023507}, pages = {2985 -- 2996}, year = {2021}, 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} } @inproceedings{DeyElsenFerreinetal.2021, author = {Dey, Thomas and Elsen, Ingo and Ferrein, Alexander and Frauenrath, Tobias and Reke, Michael and Schiffer, Stefan}, title = {CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom}, series = {PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference}, booktitle = {PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference}, editor = {Makedon, Fillia}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {9781450387927}, doi = {10.1145/3453892.3462697}, pages = {292 -- 299}, year = {2021}, abstract = {In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.}, 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} } @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{AltherrConzenElsenetal.2023, author = {Altherr, Lena and Conzen, Max and Elsen, Ingo and Frauenrath, Tobias and Lyrmann, Andreas}, title = {Sensor retrofitting of existing buildings in an interdisciplinary teaching project at university level}, series = {Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel}, booktitle = {Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Schwarz, Andr{\´e}}, publisher = {le-tex publishing services GmbH}, address = {Leipzig}, isbn = {978-3-910103-01-6}, doi = {10.33968/2023.04}, pages = {31 -- 40}, year = {2023}, abstract = {Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems}, language = {en} } @inproceedings{NethSchubaBrodkorbetal.2023, author = {Neth, Jannik and Schuba, Marko and Brodkorb, Karsten and Neugebauer, Georg and H{\"o}ner, Tim and Hack, Sacha}, title = {Digital forensics triage app for android}, series = {ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security}, booktitle = {ARES '23: Proceedings of the 18th International Conference on Availability, Reliability and Security}, publisher = {ACM}, isbn = {9798400707728}, doi = {10.1145/3600160.3605017}, pages = {6 Seiten}, year = {2023}, abstract = {Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator - without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.}, language = {en} } @inproceedings{GrundAltherr2023, author = {Grund, Raphael M. and Altherr, Lena}, title = {Development of an open source energy disaggregation tool for the home automation platform Home Assistant}, series = {Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel}, booktitle = {Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Schwarz, Andr{\´e}}, publisher = {le-tex publishing services GmbH}, address = {Leipzig}, isbn = {978-3-910103-01-6}, doi = {10.33968/2023.02}, pages = {11 -- 20}, year = {2023}, abstract = {In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.}, language = {en} } @inproceedings{AltherrDoeringFrauenrathetal.2024, author = {Altherr, Lena and D{\"o}ring, Bernd and Frauenrath, Tobias and Groß, Rolf and Mohan, Nijanthan and Oyen, Marc and Schnittcher, Lukas and Voß, Norbert}, title = {DiggiTwin: ein interdisziplin{\"a}res Projekt zur Nutzung digitaler Zwillinge auf dem Weg zu einem klimaneutralen Geb{\"a}udebestand}, series = {Tagungsband AALE 2024 : Fit f{\"u}r die Zukunft: praktische L{\"o}sungen f{\"u}r die industrielle Automation}, booktitle = {Tagungsband AALE 2024 : Fit f{\"u}r die Zukunft: praktische L{\"o}sungen f{\"u}r die industrielle Automation}, editor = {Reiff-Stephan, J{\"o}rg and J{\"a}kel, Jens and Schwarz, Andr{\´e}}, publisher = {le-tex publishing services GmbH}, address = {Leipzig}, isbn = {978-3-910103-02-3}, doi = {10.33968/2024.67}, pages = {341 -- 346}, year = {2024}, abstract = {Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Geb{\"a}udeoptimierung. Grundlage f{\"u}r eine ganzheitliche Geb{\"a}ude{\"u}berwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplin{\"a}re Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgeb{\"a}ude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Geb{\"a}udezwilling entsteht. Dieser kann zur Optimierung des Geb{\"a}udebetriebs herangezogen werden, sowie als Basis f{\"u}r eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und k{\"u}nstlicher Intelligenz kann so ein pr{\"a}zises Monitoring wichtiger Geb{\"a}udedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Geb{\"a}udezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Geb{\"a}uden untersucht und konkrete L{\"o}sungen f{\"u}r die Geb{\"a}udeoptimierung entwickelt.}, language = {de} }