TY - GEN A1 - Weiss, Nils T1 - Vulnerabilities of Connected Cars and beyond T2 - Applied Research Colloquium, 2019, Università Padua, Italy Y1 - 2019 ER - TY - CHAP A1 - Weiss, Nils A1 - Schrötter, Markus A1 - Hackenberg, Rudolf ED - Hof, Hans-Joachim ED - Fritz, Mario ED - Krauß, Christoph ED - Wasenmüller, Oliver T1 - On Threat Analysis and Risk Estimation of Automotive Ransomware T2 - ACM Computer Science in Cars Symposium : [CSCS '19) 08.10.2019, Kaiserslautern, Germany Y1 - 2019 SN - 9781450370042 U6 - https://doi.org/10.1145/3359999.3360492 SP - 1 EP - 9 PB - ACM CY - New York, NY, USA ER - TY - CHAP A1 - Graf, Julian A1 - Neubauer, Katrin A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf T1 - Architecture of an intelligent Intrusion Detection System for Smart Home T2 - 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops): 2020, Austin, Texas, USA N2 - Increasing cyber-attacks on Internet of Things (IoT) environments are a growing problem of digitized households worldwide. The purpose of this study is to investigate how an intelligent Intrusion Detection System (iIDS) can provide more security in IoT networks with a novel architecture, combining multiple classical and machine learning approaches. By combining classical security analysis methods and modern concepts of artificial intelligence, we increase the quality of attack detection and can therefore conduct dedicated attack suppression. The architectural image of the iIDS consists of different layers, which in parts achieve self-sufficient results. The results of the different modules are calculated by means of statement variables and evaluation techniques adapted for the individual module elements and subsequently combined by limit value considerations. The architecture image combines approaches for the analysis and processing of IoT network traffic and evaluates it to an aggregated score. From this result it can be determined whether the analyzed data indicates device misuse or attempted break-ins into the network. This study answers the questions whether a connection between classical and modern concepts for monitoring and analyzing IoT network traffic can be implemented meaningfully within a reliable architecture of an iIDS. KW - Internet of Things KW - artificial intelligence KW - smart Home KW - Intrusion KW - Detection System Y1 - 2020 SN - 978-1-7281-4716-1 U6 - https://doi.org/10.1109/PerComWorkshops48775.2020.9156168 SP - 1 EP - 6 PB - IEEE ER - TY - JOUR A1 - Hinterberger, Lukas A1 - Fischer, Sebastian A1 - Weber, Bernhard A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - Extended Definition of the Proposed Open Standard for IoT Device IdentificAtion and RecoGnition (IoTAG) JF - International Journal on Advances in Internet Technology N2 - Internet of Things (IoT) devices are critical to operate and maintain, because of their number and high connectivity. A lot of security issues concern IoT devices and the networks they are integrated. To help getting an overview of an IoT network, the devices and the security, we propose a scoring system to get a good impression of IT security. This system generates single scores for each device, using features like encryption, update behavior, etc. Furthermore, a summarized score for the whole network is calculated, to show the status of the network security in an easy way for the administrator. To enable the scoring system, a precise list of the existing devices and their operating status is necessary. To achieve this, we present an open standard for the IoT Device IdentificAtion and RecoGnition (short IoTAG), which requires that devices report, e.g., their name, an unique ID, the firmware version and the supported encryption. The proposed standard is described in detail and an implementation guideline is given in this paper. Additionally, information about how to realize the serialization, the integrity and the communication with IoTAG. KW - Internet of Things KW - device identification KW - open standard KW - security rating KW - IoTAG Y1 - 2020 UR - https://www.thinkmind.org/articles/inttech_v13_n34_2020_2.pdf VL - 13 IS - 3 & 4 SP - 110 EP - 121 PB - IARIA ER - TY - CHAP A1 - Neubauer, Katrin A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf ED - Trinitis, Carsten ED - Pionteck, Thilo T1 - Work in Progress: Security Analysis for Safety-critical Systems BT - Smart Grid and IoT T2 - ARCS Workshop 2019; 32nd International Conference on Architecture of Computing Systems, May 2019, Copenhagen, Denmark, Workshop FORMUS³IC N2 - Internet of Thing (IoT) and Smart Grid (SG) are separate technologies. The digital transformation of the energy industry and the increasing digitalization in the private sector connect these technologies. Currently in Germany, the SG is under construction. In order to use future innovative services, SG and IoT must be combined. For this, we connect the SG Infrastructure with the IoT. A potential insecure device and network (IoT) should be able to transfer data to and from a critical infrastructure (SG). Open research question in this context are the security requirements architecture SG and IoT and the mechanism for authentication and authorisation in future application (SG and IoT). Due to the increasing networking of the systems (SG and IoT) new threats and attack vectors arise. The attacks to the architecture influence the target of authenticity, security and privacy. For the security analysis we focus on two communication points: the communication between the smart meter gateway, and the IoT device. In our example, a connected charging station with cloud services is connected with a SG infrastructure. To create a really smart service, the charging station needs a connection to the SG to get the current amount of renewable energy in the grid. With this two connections, new threats emerge. A security analysis over all the connections, including the vulnerability and the ability of an attacker, is developed in this paper. The analysis shows us challenges of the communication between IoT and SG. For this, we defined technical and organizational requirements for authentication and authorization. Current authentication and authorization mechanisms are no longer sufficient for the defined requirements. We present the Role-based trust model for Safety-critical Systems for these defined requirements. The new trust model is integrated into a role-based access control model. It defines data classes, which separate the sensitive and non-sensitive information. KW - smart grid KW - Internet of Things (IoT) KW - security analysis; KW - safety-critical infrastructure KW - trust model Y1 - 2019 SN - 978-3-8007-4957-7 SP - 101 EP - 106 PB - VDE Verlag GmbH CY - Berlin ER - TY - CHAP A1 - Vogl, Peter A1 - Weber, Sergei A1 - Graf, Julian A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - Design and Implementation of an Intelligent and Model-based Intrusion Detection System for Iot Networks 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 - The ongoing digitization and digitalization entails the increasing risk of privacy breaches through cyber attacks. Internet of Things (IoT) environments often contain devices monitoring sensitive data such as vital signs, movement or surveil-lance data. Unfortunately, many of these devices provide limited security features. The purpose of this paper is to investigate how artificial intelligence and static analysis can be implemented in practice-oriented intelligent Intrusion Detection Systems to monitor IoT networks. In addition, the question of how static and dynamic methods can be developed and combined to improve net-work attack detection is discussed. The implementation concept is based on a layer-based architecture with a modular deployment of classical security analysis and modern artificial intelligent methods. To extract important features from the IoT network data a time-based approach has been developed. Combined with network metadata these features enhance the performance of the artificial intelligence driven anomaly detection and attack classification. The paper demonstrates that artificial intelligence and static analysis methods can be combined in an intelligent Intrusion Detection System to improve the security of IoT environments. KW - Intrusion Detection KW - Artificial Intelligence KW - Machine Learning KW - Network Security KW - Internet of Things Y1 - 2022 UR - https://www.thinkmind.org/index.php?view=article&articleid=cloud_computing_2022_1_20_28003 SN - 978-1-61208-948-5 SP - 7 EP - 12 PB - IARIA CY - [Wilmington, DE, USA] ER - TY - CHAP A1 - Hinterberger, Lukas A1 - Weber, Bernhard A1 - Fischer, Sebastian A1 - Neubauer, Katrin A1 - Hackenberg, Rudolf T1 - IoT Device IdentificAtion and RecoGnition (IoTAG) T2 - CLOUD COMPUTING 2020, The Eleventh International Conference on Cloud Computing, GRIDs and Virtualization N2 - To ensure the secure operation of IoT devices in the future, they must be continuously monitored. This starts with an inventory of the devices, checking for a current software version and extends to the encryption algorithms and active services used. Based on this information, a security analysis and rating of the whole network is possible. To solve this challenge in the growing network environments, we present a proposal for a standard. With the IoT Device IdentificAtion and RecoGnition (IoTAG), each IoT device reports its current status to a central location as required and provides information on security. This information includes a unique ID, the exact device name, the current software version, active services, cryptographic methods used, etc. The information is signed to make misuse more difficult and to ensure that the device can always be uniquely identified. In this paper, we introduce IoTAG in detail and describe the necessary requirements. KW - Internet of Things KW - device identification KW - IoTAG KW - security rating Y1 - 2020 UR - https://thinkmind.org/articles/cloud_computing_2020_2_10_28002.pdf SN - 978-1-61208-778-8 SP - 17 EP - 23 PB - IARIA ER - TY - JOUR A1 - Fuxen, Philipp A1 - Schönhärl, Stefan A1 - Schmidt, Jonas A1 - Gerstner, Mathias A1 - Jahn, Sabrina A1 - Graf, Julian A1 - Hackenberg, Rudolf A1 - Mottok, Jürgen T1 - A Cybersecurity Education Platform for Automotive Penetration Testing JF - International Journal On Advances in Security N2 - The paper presents a penetration testing framework for automotive IT security education and evaluates its realization. The automotive sector is changing due to automated driving functions, connected vehicles, and electric vehicles. This development also creates new and more critical vulnerabilities. This paper addresses a possible countermeasure, automotive IT security education. Some existing solutions are evaluated and compared with the created Automotive Penetration Testing Education Platform (APTEP) framework. In addition, the APTEP architecture is described. It consists of three layers representing different attack points of a vehicle. The realization of the APTEP is a hardware case and 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 theories, such as constructivism and problem-based/challenge-based learning. Computer Science students from the Ostbayerische Technische Hochschule (OTH) Regensburg experienced the challenges as part of a elective subject. In an online survey evaluated in this paper, they gave positive feedback. Also, a part of the evaluation is the mapping of the ANSKo and the maturity levels in the Software Assurance Maturity Model (SAMM) practice Education & Guidance as well as the SAMM practice Security Testing. The scientific contribution of this paper is to present an APTEP, a corresponding learning concept and an evaluation method. KW - Challenge-based Learning KW - Education Framework KW - Penetration Testing KW - Automotive KW - IT-Security Education Y1 - 2022 UR - http://www.iariajournals.org/security/sec_v15_n34_2022_paged.pdf SN - 1942-2636 VL - 15 IS - 3&4 SP - 106 EP - 118 PB - IARIA ER - TY - CHAP A1 - Weber, Bernhard A1 - Hinterberger, Lukas A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf ED - Duncan, Bob ED - Lee, Yong Woo ED - Popescu, Manuela T1 - How to Prevent Misuse of IoTAG? T2 - Cloud Computing 2021: the Twelfth International Conference on Cloud Computing, GRIDs, and Virtualization: April 18-22, 2021, Porto, Portugal N2 - Since IoT devices are potentially insecure and offer great attack potential, in our past research we presented IoTAG, a solution where devices communicate security-related information about themselves. However, since this information can also be exploited by attackers, we present in this paper a solution against the misuse of IoTAG. In doing so, we address the two biggest problems: authentication and pairing with a trusted device. This is solved by introducing a pairing process, which uses the simultaneous authentication of equals algorithm to securely exchange and verify each others signature, and by using the server and client authentication provided by HTTP over TLS. We provide the minimum requirements and evaluate the methods used. The emphasis is on known and already proven methods. Additionally, we analyze the potential consequences of an attacker tapping the IoTAG information. Finally, we conclude that the solution successfully prevents access to IoTAG by unauthorized clients on the same network. KW - Internet of Things KW - IoTAG KW - device pairing KW - device authentication KW - trusted connection Y1 - 2021 UR - https://www.thinkmind.org/articles/cloud_computing_2021_1_40_28006.pdf SN - 978-1-61208-845-7 SN - 2308-4294 PB - IARIA CY - Wilmington, DE, USA ER - TY - CHAP A1 - Neubauer, Katrin A1 - Fischer, Sebastian A1 - Hackenberg, Rudolf T1 - Risk Analysis of the Cloud Infrastructure of Smart Grid and Internet of Things T2 - The Tenth International Conference on Cloud Computing, GRIDs, and Virtualization, (CLOUD COMPUTING 2019), 10th Mai 2019, Venice, Italy N2 - Cloud Computing (CC), Internet of Thing (IoT) and Smart Grid (SG) are separate technologies. The digital transformation of the energy industry and the increasing digitalization in the private sector connect these technologies. At the moment, CC is used as a service provider for IoT. Currently in Germany, the SG is under construction and a cloud connection to the infrastructure has not been implemented yet. To build the SG cloud, the new laws for privacy must be implemented and therefore it’s important to know which data can be stored and distributed over a cloud. In order to be able to use future innovative services, SG and IoT must be combined. For this, in the next step we connect the SG infrastructure with the IoT. A potential insecure device and network (IoT) should be able to transfer data to and from a critical infrastructure (SG). In detail, we focus on two different connections: the communication between the smart meter switching box and the IoT device and the data transferred between the IoT and SG cloud. In our example, a connected charging station with cloud services is connected with a SG infrastructure. To create a really smart service, the charging station needs a connection to the SG to get the current amount of renewable energy in the grid. Private data, such as name, address and payment details, should not be transferred to the IoT cloud. With these two connections, new threads emerge. In this case, availability, confidentiality and integrity must be ensured. A risk analysis over all the cloud connections, including the vulnerability and the ability of an attacker and the resulting risk are developed in this paper. KW - Smart Grid KW - Internet of Things KW - security analysis KW - cloud computing KW - safety-critical infrastructure Y1 - 2019 UR - https://www.thinkmind.org/articles/cloud_computing_2019_6_20_28013.pdf SN - 978-1-61208-703-0 SN - 2308-4294 SP - 82 EP - 87 PB - IARIA ER - 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 -