@inproceedings{BroennerHoefkenSchuba2016, author = {Broenner, Simon and H{\"o}fken, Hans-Wilhelm and Schuba, Marko}, title = {Streamlining extraction and analysis of android RAM images}, series = {Proceedings of the 2nd international conference on information systems security and privacy}, booktitle = {Proceedings of the 2nd international conference on information systems security and privacy}, organization = {ICISSP International Conference on Information Systems Security and Privacy <2, 2016, Rome, Italy>}, isbn = {978-989-758-167-0}, doi = {10.5220/0005652802550264}, pages = {255 -- 264}, year = {2016}, language = {en} } @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{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{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{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} } @inproceedings{WalterElsenMuelleretal.1999, author = {Walter, Peter and Elsen, Ingo and M{\"u}ller, Holger and Kraiss, Karl-Friedrich}, title = {3D object recognition with a specialized mixtures of experts architecture}, series = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings}, booktitle = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings}, publisher = {IEEE}, address = {New York}, isbn = {0-7803-5529-6}, issn = {1098-7576}, doi = {10.1109/IJCNN.1999.836243}, pages = {3563 -- 3568}, year = {1999}, abstract = {Aim of the AXON2 project (Adaptive Expert System for Object Recogniton using Neuml Networks) is the development of an object recognition system (ORS) capable of recognizing isolated 3d objects from arbitrary views. Commonly, classification is based on a single feature extracted from the original image. Here we present an architecture adapted from the Mixtures of Eaqerts algorithm which uses multiple neuml networks to integmte different features. During tmining each neural network specializes in a subset of objects or object views appropriate to the properties of the corresponding feature space. In recognition mode the system dynamically chooses the most relevant features and combines them with maximum eficiency. The remaining less relevant features arz not computed and do therefore not decelerate the-recognition process. Thus, the algorithm is well suited for ml-time applications.}, language = {en} } @article{ElsenKraiss1999, author = {Elsen, Ingo and Kraiss, Karl-Friedrich}, title = {System concept and realization of a scalable neurocomputing architecture}, series = {Systems Analysis Modelling Simulation}, volume = {35}, journal = {Systems Analysis Modelling Simulation}, number = {4}, publisher = {Gordon and Breach Science Publishers}, address = {Amsterdam}, issn = {0232-9298}, pages = {399 -- 419}, year = {1999}, abstract = {This paper describes the realization of a novel neurocomputer which is based on the concepts of a coprocessor. In contrast to existing neurocomputers the main interest was the realization of a scalable, flexible system, which is capable of computing neural networks of arbitrary topology and scale, with full independence of special hardware from the software's point of view. On the other hand, computational power should be added, whenever needed and flexibly adapted to the requirements of the application. Hardware independence is achieved by a run time system which is capable of using all available computing power, including multiple host CPUs and an arbitrary number of neural coprocessors autonomously. The realization of arbitrary neural topologies is provided through the implementation of the elementary operations which can be found in most neural topologies.}, language = {en} } @article{ElsenKraissKrumbiegeletal.1999, author = {Elsen, Ingo and Kraiss, Karl-Friedrich and Krumbiegel, Dirk and Walter, Peter and Wickel, Jochen}, title = {Visual information retrieval for 3D product identification: a midterm report}, series = {KI - K{\"u}nstliche Intelligenz}, volume = {13}, journal = {KI - K{\"u}nstliche Intelligenz}, number = {1}, publisher = {Springer}, address = {Berlin}, issn = {1610-1987}, pages = {64 -- 67}, year = {1999}, language = {en} } @inproceedings{Elsen1998, author = {Elsen, Ingo}, title = {A pixel based approach to view based object recognition with self-organizing neural networks}, series = {IECON'98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society}, booktitle = {IECON'98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society}, publisher = {IEEE}, address = {New York}, isbn = {0-7803-4503-7}, doi = {10.1109/IECON.1998.724032}, pages = {2040 -- 2044}, year = {1998}, abstract = {This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images.}, language = {en} } @inproceedings{ElsenKraissKrumbiegel1997, author = {Elsen, Ingo and Kraiss, Karl-Friedrich and Krumbiegel, Dirk}, title = {Pixel based 3D object recognition with bidirectional associative memories}, series = {International Conference on Neural Networks 1997}, booktitle = {International Conference on Neural Networks 1997}, publisher = {IEEE}, address = {New York}, isbn = {0-7803-4122-8}, pages = {1679 -- 1684}, year = {1997}, abstract = {This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand.}, 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{ElsenSchmalzbauer2011, author = {Elsen, Ingo and Schmalzbauer, Michael}, title = {Messsystematik zur Steuerung der Produkt- und Prozessqualit{\"a}t in Systemintegrationsprojekten - ein Erfahrungsbericht}, series = {Software Engineering 2011 - Fachtagung des GI-Fachbereichs Softwaretechnik, 21. - 25. Februar 2011 in Karlsruhe}, booktitle = {Software Engineering 2011 - Fachtagung des GI-Fachbereichs Softwaretechnik, 21. - 25. Februar 2011 in Karlsruhe}, editor = {Reussner, Ralf and Grund, Matthias and Andreas, Oberweis and Tichy, Walter}, publisher = {Gesellschaft f{\"u}r Informatik eV}, address = {Bonn}, isbn = {9783885792772}, issn = {1617-5468}, pages = {1 Seite}, year = {2011}, abstract = {Der Erfolg eines Softwarenentwicklungsprojektes insbesondere eines Systemintegrationsprojektes wird mit der Erf{\"u}llung des „Teufelsdreiecks", „In-Time", „In-Budget", „In-Quality" gemessen. Hierzu ist die Kenntnis der Software- und Prozessqualit{\"a}t essenziell, um die Einhaltung der Qualit{\"a}tskriterien festzustellen, aber auch, um eine Vorhersage hinsichtlich Termin- und Budgettreue zu treffen. Zu diesem Zweck wurde in der T-Systems Systems Integration ein System aus verschiedenen Key Performance Indikatoren entworfen und in der Organisation implementiert, das genau das leistet und die Kriterien f{\"u}r CMMI Level 3 erf{\"u}llt.}, language = {de} } @inproceedings{ElsenHawariJohnen2010, author = {Elsen, Ingo and Hawari, Asma and Johnen, Uwe}, title = {Produktkernel in der Systemintegration (Erfahrungsbericht aus der Praxis)}, series = {Vom Projekt zum Produkt - Fachtagung des GI-Fachausschusses Management der Anwendungsentwicklung und -wartung im Fachbereich Wirtschaftsinformatik (WI-MAW), 1. - 3. Dezember 2010 in Aachen}, booktitle = {Vom Projekt zum Produkt - Fachtagung des GI-Fachausschusses Management der Anwendungsentwicklung und -wartung im Fachbereich Wirtschaftsinformatik (WI-MAW), 1. - 3. Dezember 2010 in Aachen}, editor = {Pietsch, Wolfram and Krams, Benedikt}, publisher = {Gesellschaft f{\"u}r Informatik eV}, address = {Bonn}, isbn = {9783885792727}, issn = {1617-5468}, pages = {93 -- 102}, year = {2010}, abstract = {In der Vergangenheit basierten große Systemintegrationsprojekte in der Regel auf Individualentwicklungen f{\"u}r einzelne Kunden. Getrieben durch Kostendruck steigt aber der Bedarf nach standardisierten L{\"o}sungen, die gleichzeitig die individuellen Anforderungen des jeweiligen Umfelds ber{\"u}cksichtigen. T-Systems GEI GmbH wird beiden Anforderungen mit Produktkerneln gerecht. Neben den technischen Aspekten der Kernelentwicklung spielen besonders organisatorische Aspekte eine Rolle, um Kernel effizient und qualitativ hochwertig zu entwickeln, ohne deren Funktionalit{\"a}ten ins Uferlose wachsen zu lassen. Umgesetzt hat T-Systems dieses Konzept f{\"u}r Flughafeninformationssysteme. Damit kann dem wachsenden Bedarf der Flughafenbetreiber nach einer effizienten und kosteng{\"u}nstigen Softwarel{\"o}sung zur Unterst{\"u}tzung Ihrer Gesch{\"a}ftsprozesse entsprochen werden.}, language = {de} } @article{ElsenHartungHornetal.2001, author = {Elsen, Ingo and Hartung, Frank and Horn, Uwe and Kampmann, Markus and Peters, Liliane}, title = {Streaming technology in 3G mobile communication systems}, series = {Computer : innovative technology for computer professionals}, volume = {34}, journal = {Computer : innovative technology for computer professionals}, number = {9 Seiten}, editor = {Voas, Jeffrey}, publisher = {IEEE}, address = {New York}, issn = {0018-9162}, pages = {46 -- 52}, year = {2001}, abstract = {Third-generation mobile communication systems will combine standardized streaming with a range of unique services to provide high-quality Internet content that meets the specific needs of the rapidly growing mobile market.}, language = {en} } @phdthesis{Elsen2000, author = {Elsen, Ingo}, title = {Ansichtenbasierte 3D-Objekterkennung mit erweiterten selbstorganisierenden Merkmalskarten}, publisher = {VDI-Verlag}, address = {D{\"u}sseldorf}, isbn = {978-3-18-363110-0}, issn = {0341-1796}, pages = {VIII, 140 S. : Ill., graph. Darst.}, year = {2000}, language = {de} } @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{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} }