TY - CHAP A1 - Fischer, Sebastian A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - A Study about the Different Categories of IoT in Scientific Publications T2 - CLOUD COMPUTING 2020: the Eleventh International Conference on Cloud Computing, GRIDs and Virtualization, October 25-29, 2020, Nizza N2 - The Internet of Things (IoT) is widely used as a synonym for nearly every connected device. This makes it really difficult to find the right kind of scientific publication for the intended category of IoT. Conferences and other events for IoT are confusing about the target group (consumer, enterprise, industrial, etc.) and standardisation organisations suffer from the same problem. To demonstrate these problems, this paper shows the results of an analyses over IoT publications in different research libraries. The number of results for IoT, consumer, enterprise and industrial search queries were evaluated and a manual study about 100 publications was done. According to the research library or search engine, different results about the distribution of consumer-, enterprise- and industrial- IoT are visible. The comparison with the results of the manual evaluation shows that some search queries do not show all desired publications or that considerably more, unwanted results are returned. Most researchers do not use the keywords right and the exact category of IoT can only be accessed via the abstract. This shows major problems with the use of the term IoT and its minor limitations. KW - Internet of Things KW - IoT KW - publications KW - consumer KW - industrial KW - enterprise KW - categorization Y1 - 2020 UR - https://thinkmind.org/articles/cloud_computing_2020_2_20_28004.pdf SN - 978-1-61208-778-8 SP - 24 EP - 30 PB - IARIA ER - TY - CHAP A1 - Fuxen, Philipp A1 - Hackenberg, Rudolf A1 - Heinl, M. P. A1 - Schunck, C. H. A1 - Yahalom, R. T1 - MANTRA: A Graph-based Unified Information Aggregation Foundation for Enhancing Cybersecurity Management in Critical Infrastructures // Aufsatznr.: P-335 T2 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), N2 - The digitization of almost all sectors of life and the quickly growing complexity of interrelationships between actors in this digital world leads to a dramatically increasing attack surface regarding both direct and also indirect attacks over the supply chain. These supply chain attacks can have different characters, e.g., vulnerabilities and backdoors in hardware and software, illegitimate access by compromised service providers, or trust relationships to suppliers and customers exploited in the course of business email compromise. To address this challenge and create visibility along these supply chains, threat-related data needs to be rapidly exchanged and correlated over organizational borders. The publicly funded project MANTRA is meant to create a secure and resilient framework for real-time exchange of cyberattack patterns and automated, contextualized risk management. The novel graph-based approach provides benefits for automation regarding cybersecurity management, especially when it comes to prioriization of measures for risk reduction and during active defense against cyberattacks. In this paper, we outline MANTRA’s scope, objectives, envisioned scientific approach, and challenges. Y1 - 2023 U6 - https://doi.org/10.18420/OID2023_10 SP - 123 EP - 128 ER - TY - CHAP A1 - Gerstner, Mathias A1 - Hackenberg, Rudolf T1 - Context-aware forecasting of mobile network quality for autonomous vehicle connectivity T2 - Vehicular analytics 2025 : the second conference on vehicular systems N2 - As autonomous driving becomes increasingly feasible, the German government has introduced a legal framework to enable the operation with Level 4 automated driving functionality. A key requirement is the maintenance of a continuous connection between such vehicles and a remote technical supervisor. If this link is lost, the vehicle must transition into a safe state by bringing itself to a controlled stop. To mitigate the risk of connection loss, accurate forecasting of mobile network availability along routes is essential. This paper presents an Exploratory Data Analysis (EDA) based on 38 measurement runs collected over ten months along a rural 64 km route in Germany. The dataset includes passive mobile network signal quality parameters, Global Navigation Satellite System (GNSS) position and precision data, as well as contextual features, such as speed, driving direction, day of the week, weather, and distance to the connected base station. Although mean values capture overall tendencies for areas with consistently good or poor coverage, they fail to capture the variability necessary for reliable prediction on a per-trip basis. Notably, some route segments show high variance in signal quality across different measurement runs. This variability is assumed to result from changing environmental influences, such as weather or traffic conditions at different times. Our analysis reveals weak but statistically relevant correlations between several contextual features (e.g., temperature ≈ -0.2) and network quality indicators. The inclusion of weather parameters or the day of the week has been shown to lower the Mean Absolute Error (MAE) compared to a prediction based only on measurements from the past. These findings underscore the importance of contextual information and localized modeling to predict network availability for safety-critical systems, such as autonomous vehicles. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-86166 UR - https://www.thinkmind.org/library/VEHICULAR_ANALYTICS/VEHICULAR_ANALYTICS_2025/vehicular_analytics_2025_1_10_30005.html SN - 978-1-68558-320-0 PB - IARIA ER - TY - CHAP A1 - Schönhärl, Stefan A1 - Fuxen, Philipp A1 - Graf, Julian A1 - Schmidt, Jonas A1 - Hackenberg, Rudolf A1 - Mottok, Jürgen T1 - An Automotive Penetration Testing Framework for IT-Security Education T2 - Cloud Computing 2022: The Thirteenth International Conference on Cloud Computing, GRIDs, and Virtualization, Special Track FAST-CSP, Barcelona, Spain, 24.-28.04.2022 N2 - Automotive Original Equipment Manufacturer (OEM) and suppliers started shifting their focus towards the security of their connected electronic programmable products recently since cars used to be mainly mechanical products. However, this has changed due to the rising digitalization of vehicles. Security and functional safety have grown together and need to be addressed as a single issue, referred to as automotive security, in the following article. One way to accomplish security is automotive security education. The scientific contribution of this paper is to establish an Automotive Penetration Testing Education Platform (APTEP). It consists of three layers representing different attack points of a vehicle. The layers are the outer, inner, and core layers. Each of those contains multiple interfaces, such as Wireless Local Area Network (WLAN) or electric vehicle charging interfaces in the outer layer, message bus systems in the inner layer, and debug or diagnostic interfaces in the core layer. One implementation of APTEP is in a hardware case and as a virtual platform, referred to as the Automotive Network Security Case (ANSKo). The hardware case contains emulated control units and different communication protocols. The virtual platform uses Docker containers to provide a similar experience over the internet. Both offer two kinds of challenges. The first introduces users to a specific interface, while the second combines multiple interfaces, to a complex and realistic challenge. This concept is based on modern didactic theory, such as constructivism and problem-based learning. Computer Science students from the Ostbayerische Technische Hochschule (OTH)Regensburg experienced the challenges as part of a special topic course and provided positive feedback. KW - IT-Security KW - Education KW - Automotive KW - Penetration testing KW - Education framework Y1 - 2022 UR - https://www.thinkmind.org/index.php?view=article&articleid=cloud_computing_2022_1_10_28001 SN - 978-1-61208-948-5 SP - 1 EP - 6 PB - IARIA CY - [Wilmington, DE, USA] ER -