This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2024-04-25 Creation time: 08-46-23 --- Number of references 22 inproceedings 2023_lohmoeller_transparency 2023 11 27 data usage control; data ecosystems; transparency logs https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-lohmoeller-transparency.pdf ACM Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS ’23), November 26-30, 2023, Copenhagen, Denmark Copenhagen, Denmark November 26-30, 2023 979-8-4007-0050-7/23/11 10.1145/3576915.3624371 1 JohannesLohmöller EduardVlad MarkusDahlmanns KlausWehrle inproceedings 2023_matzutt_street_problems 2023 11 27 3591-3593 Municipalities increasingly depend on citizens to file digital reports about issues such as potholes or illegal trash dumps to improve their response time. However, the responsible authorities may be incentivized to ignore certain reports, e.g., when addressing them inflicts high costs. In this work, we explore the applicability of blockchain technology to hold authorities accountable regarding filed reports. Our initial assessment indicates that our approach can be extended to benefit citizens and authorities in the future. street problems; accountability; consortium blockchain; privacy https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-matzutt-street-problems.pdf ACM Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS ’23), November 26-30, 2023, Copenhagen, Denmark Copenhagen, Denmark November 26-30, 2023 979-8-4007-0050-7/23/11 10.1145/3576915.3624367 1 RomanMatzutt JanPennekamp KlausWehrle inproceedings 2023_sloun_accessibility 2023 11 27 3543-3545 The generation of datasets is one of the most promising approaches to collecting the necessary behavior data to train machine learning models for host-based intrusion detection. While various dataset generation methods have been proposed, they are often limited and either only generate network traffic or are restricted to a narrow subset of applications. We present Vulcan, a preliminary framework that uses accessibility features to generate datasets by simulating user interactions for an extendable set of applications. It uses behavior profiles that define realistic user behavior and facilitate dataset updates upon changes in software versions, thus reducing the effort required to keep a dataset relevant. Preliminary results show that using accessibility features presents a promising approach to improving the quality of datasets in the HIDS domain. Intrusion Detection, Dataset Generation, Accessibility Features https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-sloun-vulcan-accessibility.pdf ACM Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS '23), November 26-30, 2023, Copenhagen, Denmark Copenhagen, Denmark November 26-30, 2023 979-8-4007-0050-7/23/11 10.1145/3576915.3624404 1 Christianvan Sloun KlausWehrle article 2023_pennekamp_purchase_inquiries ACM Transactions on Internet Technology 2023 11 17 23 4 Dynamic and flexible business relationships are expected to become more important in the future to accommodate specialized change requests or small-batch production. Today, buyers and sellers must disclose sensitive information on products upfront before the actual manufacturing. However, without a trust relation, this situation is precarious for the involved companies as they fear for their competitiveness. Related work overlooks this issue so far: Existing approaches only protect the information of a single party only, hindering dynamic and on-demand business relationships. To account for the corresponding research gap of inadequately privacy-protected information and to deal with companies without an established trust relation, we pursue the direction of innovative privacy-preserving purchase inquiries that seamlessly integrate into today's established supplier management and procurement processes. Utilizing well-established building blocks from private computing, such as private set intersection and homomorphic encryption, we propose two designs with slightly different privacy and performance implications to securely realize purchase inquiries over the Internet. In particular, we allow buyers to consider more potential sellers without sharing sensitive information and relieve sellers of the burden of repeatedly preparing elaborate yet discarded offers. We demonstrate our approaches' scalability using two real-world use cases from the domain of production technology. Overall, we present deployable designs that offer two-way privacy for purchase inquiries and, in turn, fill a gap that currently hinders establishing dynamic and flexible business relationships. In the future, we expect significantly increasing research activity in this overlooked area to address the needs of an evolving production landscape. bootstrapping procurement; secure industrial collaboration; private set intersection; homomorphic encryption; Internet of Production internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-purchase-inquiries.pdf ACM 1533-5399 10.1145/3599968 1 JanPennekamp MarkusDahlmanns FrederikFuhrmann TimoHeutmann AlexanderKreppein DennisGrunert ChristophLange Robert H.Schmitt KlausWehrle inproceedings 2023_bader_reputation-systems 2023 11 Consumers frequently interact with reputation systems to rate products, services, and deliveries. While past research extensively studied different conceptual approaches to realize such systems securely and privacy-preservingly, these concepts are not yet in use in business-to-business environments. In this paper, (1) we thus outline which specific challenges privacy-cautious stakeholders in volatile supply chain networks introduce, (2) give an overview of the diverse landscape of privacy-preserving reputation systems and their properties, and (3) based on well-established concepts from supply chain information systems and cryptography, we further propose an initial concept that accounts for the aforementioned challenges by utilizing fully homomorphic encryption. For future work, we identify the need of evaluating whether novel systems address the supply chain-specific privacy and confidentiality needs. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST) SCM; confidentiality; anonymity; voter; votee; FHE internet-of-production https://jpennekamp.de/wp-content/papercite-data/pdf/bpt+23.pdf Springer Proceedings of the 20th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous '23), November 14-17, 2023, Melbourne, VIC, Australia Melbourne, VIC, Australia November 14-17, 2023 accepted 1867-8211 1 LennartBader JanPennekamp EmildeonThevaraj MariaSpiß Salil S.Kanhere KlausWehrle article 2023_lamberts_metrics-sok Journal of Systems Research 2023 10 31 3 1 Industrial systems are increasingly threatened by cyberattacks with potentially disastrous consequences. To counter such attacks, industrial intrusion detection systems strive to timely uncover even the most sophisticated breaches. Due to its criticality for society, this fast-growing field attracts researchers from diverse backgrounds, resulting in 130 new detection approaches in 2021 alone. This huge momentum facilitates the exploration of diverse promising paths but likewise risks fragmenting the research landscape and burying promising progress. Consequently, it needs sound and comprehensible evaluations to mitigate this risk and catalyze efforts into sustainable scientific progress with real-world applicability. In this paper, we therefore systematically analyze the evaluation methodologies of this field to understand the current state of industrial intrusion detection research. Our analysis of 609 publications shows that the rapid growth of this research field has positive and negative consequences. While we observe an increased use of public datasets, publications still only evaluate 1.3 datasets on average, and frequently used benchmarking metrics are ambiguous. At the same time, the adoption of newly developed benchmarking metrics sees little advancement. Finally, our systematic analysis enables us to provide actionable recommendations for all actors involved and thus bring the entire research field forward. internet-of-production, rfc https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-lamberts-metrics-sok.pdf eScholarship Publishing 2770-5501 10.5070/SR33162445 1 OlavLamberts KonradWolsing EricWagner JanPennekamp JanBauer KlausWehrle MartinHenze inproceedings 2023-kunze-spin-bit-in-the-wild 2023 10 https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-kunze-spin-bit-in-the-wild.pdf ACM Proceedings of the Internet Measurement Conference (IMC '23) Internet Measurement Conference 2023 10.1145/3618257.3624844 1 IkeKunze ConstantinSander KlausWehrle inproceedings 2023-sander-quic-ecn 2023 10 legato https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-sander-quic-ecn.pdf https://arxiv.org/abs/2309.14273 ACM Proceedings of the Internet Measurement Conference (IMC '23) Internet Measurement Conference 2023 979-8-4007-0382-9/23/10 10.1145/3618257.3624821 1 ConstantinSander IkeKunze LeoBlöcher MikeKosek KlausWehrle inproceedings 2023-wagner-lcn-repel 2023 10 https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-wagner-repel.pdf IEEE 48th IEEE Conference on Local Computer Networks (LCN), Daytona Beach, Florida, US Daytona Beach, Florida, US IEEE Conference on Local Computer Networks (LCN) Oktober 1-5, 2023 accepted en 1 EricWagner NilsRothaug KonradWolsing LennartBader KlausWehrle MartinHenze inproceedings 2023-wolsing-xluuvlab 2023 10 Roughly two-thirds of our planet is covered with water, and so far, the oceans have predominantly been used at their surface for the global transport of our goods and commodities. Today, there is a rising trend toward subsea infrastructures such as pipelines, telecommunication cables, or wind farms which demands potent vehicles for underwater work. To this end, a new generation of vehicles, large and Extra-Large Unmanned Underwater Vehicles (XLUUVs), is currently being engineered that allow for long-range, remotely controlled, and semi-autonomous missions in the deep sea. However, although these vehicles are already heavily developed and demand state-of-the-art communi- cation technologies to realize their autonomy, no dedicated test and development environments exist for research, e.g., to assess the implications on cybersecurity. Therefore, in this paper, we present XLab-UUV, a virtual testbed for XLUUVs that allows researchers to identify novel challenges, possible bottlenecks, or vulnerabilities, as well as to develop effective technologies, protocols, and procedures. Maritime Simulation Environment, XLUUV, Cyber Range, Autonomous Shipping, Operational Technology https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-wolsing-xluuvlab.pdf IEEE 1st IEEE LCN Workshop on Maritime Communication and Security (MarCaS) Daytona Beach, Florida, USA 1st IEEE LCN Workshop on Maritime Communication and Security (MarCaS) Oktober 1-5, 2023 accepted en 10.1109/LCN58197.2023.10223405 1 KonradWolsing AntoineSaillard ElmarPadilla JanBauer inproceedings 2023-redefine-mpc-cosimulation Proceedings of the 14th IEEE International Conference on Smart Grid Communications (SmartGridComm 2023) 2023 10 redefine IEEE Proceedings of the 14th IEEE International Conference on Smart Grid Communications (SmartGridComm 2023) accepted 1 TobiasHeins RenéGlebke MirkoStoffers SriramGurumurthy JanHeesemann MartinaJosevski AntonelloMonti KlausWehrle inproceedings 2023-bader-metrics 2023 9 28 https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-bader-metrics.pdf Proceedings of the 9th Workshop on the Security of Industrial Control Systems & of Cyber-Physical Systems (CyberICPS '23), co-located with the the 28th European Symposium on Research in Computer Security (ESORICS '23) The Hague, The Netherlands 9th Workshop on the Security of Industrial Control Systems & of Cyber-Physical Systems (CyberICPS '23) September 28, 2023 accepted 10.1007/978-3-031-54204-6_2 1 LennartBader EricWagner MartinHenze MartinSerror inproceedings 2023_wolsing_ensemble 2023 9 25 14345 102-122 Industrial Intrusion Detection Systems (IIDSs) play a critical role in safeguarding Industrial Control Systems (ICSs) against targeted cyberattacks. Unsupervised anomaly detectors, capable of learning the expected behavior of physical processes, have proven effective in detecting even novel cyberattacks. While offering decent attack detection, these systems, however, still suffer from too many False-Positive Alarms (FPAs) that operators need to investigate, eventually leading to alarm fatigue. To address this issue, in this paper, we challenge the notion of relying on a single IIDS and explore the benefits of combining multiple IIDSs. To this end, we examine the concept of ensemble learning, where a collection of classifiers (IIDSs in our case) are combined to optimize attack detection and reduce FPAs. While training ensembles for supervised classifiers is relatively straightforward, retaining the unsupervised nature of IIDSs proves challenging. In that regard, novel time-aware ensemble methods that incorporate temporal correlations between alerts and transfer-learning to best utilize the scarce training data constitute viable solutions. By combining diverse IIDSs, the detection performance can be improved beyond the individual approaches with close to no FPAs, resulting in a promising path for strengthening ICS cybersecurity. Lecture Notes in Computer Science (LNCS), Volume 14345 Intrusion Detection; Ensemble Learning; ICS internet-of-production, rfc https://jpennekamp.de/wp-content/papercite-data/pdf/wkw+23.pdf Springer Proceedings of the 28th European Symposium on Research in Computer Security (ESORICS '23), September 25-29, 2023, The Hague, The Netherlands The Hague, The Netherlands 28th European Symposium on Research in Computer Security (ESORICS '23) September 25-29, 2023 978-3-031-51475-3 0302-9743 10.1007/978-3-031-51476-0_6 1 KonradWolsing DominikKus EricWagner JanPennekamp KlausWehrle MartinHenze inproceedings 2023_bodenbenner_fairsensor 2023 7 20 The long-term utility and reusability of measurement data from production processes depend on the appropriate contextualization of the measured values. These requirements further mandate that modifications to the context need to be recorded. To be (re-)used at all, the data must be easily findable in the first place, which requires arbitrary filtering and searching routines. Following the FAIR guiding principles, fostering findable, accessible, interoperable and reusable (FAIR) data, in this paper, the FAIR Sensor Ecosystem is proposed, which provides a contextualization middleware based on a unified data metamodel. All information and relations which might change over time are versioned and associated with temporal validity intervals to enable full reconstruction of a system's state at any point in time. A technical validation demonstrates the correctness of the FAIR Sensor Ecosystem, including its contextualization model and filtering techniques. State-of-the-art FAIRness assessment frameworks rate the proposed FAIR Sensor Ecosystem with an average FAIRness of 71%. The obtained rating can be considered remarkable, as deductions mainly result from the lack of fully appropriate FAIRness metrics and the absence of relevant community standards for the domain of the manufacturing industry. FAIR Data; Cyber-Physical Systems; Data Management; Data Contextualization; Internet of Production internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-bodenbenner-fair-ecosystem.pdf IEEE Proceedings of the 21th IEEE International Conference on Industrial Informatics (INDIN '23), July 17-20, 2023, Lemgo, Germany Lemgo, Germany July 17-20, 2023 978-1-6654-9313-0 2378-363X 10.1109/INDIN51400.2023.10218149 1 MatthiasBodenbenner JanPennekamp BenjaminMontavon KlausWehrle Robert H.Schmitt inproceedings 2023-dahlmanns-docker 2023 7 10 797-811 Containerization allows bundling applications and their dependencies into a single image. The containerization framework Docker eases the use of this concept and enables sharing images publicly, gaining high momentum. However, it can lead to users creating and sharing images that include private keys or API secrets—either by mistake or out of negligence. This leakage impairs the creator's security and that of everyone using the image. Yet, the extent of this practice and how to counteract it remains unclear. In this paper, we analyze 337,171 images from Docker Hub and 8,076 other private registries unveiling that 8.5% of images indeed include secrets. Specifically, we find 52,107 private keys and 3,158 leaked API secrets, both opening a large attack surface, i.e., putting authentication and confidentiality of privacy-sensitive data at stake and even allow active attacks. We further document that those leaked keys are used in the wild: While we discovered 1,060 certificates relying on compromised keys being issued by public certificate authorities, based on further active Internet measurements, we find 275,269 TLS and SSH hosts using leaked private keys for authentication. To counteract this issue, we discuss how our methodology can be used to prevent secret leakage and reuse. network security; security configuration; secret leakage; container ven2us, internet-of-production, https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-dahlmanns-asiaccs.pdf ACM Proceedings of the 2023 ACM Asia Conference on Computer and Communications Security (ASIACCS '23), July 10-14, 2023, Melbourne, VIC, Australia Melbourne, VIC, Australia ASIA CCS '23 July 10-14, 2023 979-8-4007-0098-9/23/07 10.1145/3579856.3590329 1 MarkusDahlmanns ConstantinSander RobinDecker KlausWehrle inproceedings 2023_pennekamp_benchmarking_comparison 2023 6 15 13901 489-505 Benchmarking is an essential tool for industrial organizations to identify potentials that allows them to improve their competitive position through operational and strategic means. However, the handling of sensitive information, in terms of (i) internal company data and (ii) the underlying algorithm to compute the benchmark, demands strict (technical) confidentiality guarantees—an aspect that existing approaches fail to address adequately. Still, advances in private computing provide us with building blocks to reliably secure even complex computations and their inputs, as present in industry benchmarks. In this paper, we thus compare two promising and fundamentally different concepts (hardware- and software-based) to realize privacy-preserving benchmarks. Thereby, we provide detailed insights into the concept-specific benefits. Our evaluation of two real-world use cases from different industries underlines that realizing and deploying secure information systems for industry benchmarking is possible with today's building blocks from private computing. Lecture Notes in Computer Science (LNCS), Volume 13901 real-world computing; trusted execution environments; homomorphic encryption; key performance indicators; benchmarking internet-of-production https://jpennekamp.de/wp-content/papercite-data/pdf/plv+23.pdf Springer Proceedings of the 35th International Conference on Advanced Information Systems Engineering (CAiSE '23), June 12-16, 2023, Zaragoza, Spain Zaragoza, Spain 35th International Conference on Advanced Information Systems Engineering (CAiSE '23) June 12-16, 2023 978-3-031-34559-3 0302-9743 10.1007/978-3-031-34560-9_29 1 JanPennekamp JohannesLohmöller EduardVlad JoschaLoos NiklasRodemann PatrickSapel Ina BereniceFink SethSchmitz ChristianHopmann MatthiasJarke GüntherSchuh KlausWehrle MartinHenze inproceedings 2023-grote-mvca-fairness 2023 6 https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-grote-mvca-fairness.pdf IFIP/IEEE Proceedings of the Network Traffic Measurement and Analysis Conference (TMA '23) 978-3-903176-58-4 10.23919/TMA58422.2023.10199019 1 LaurenzGrote IkeKunze ConstantinSander KlausWehrle article 2023-circres-wu-comp-ecosystem Circulation research 2023 4 14 132 8 1084-1100 Online en 10.1161/CIRCRESAHA.123.321765 1 ZhuojunWu JohannesLohmöller ChristianeKuhl KlausWehrle JoachimJankowski incollection 2023_pennekamp_crd-a.i 2023 2 8 35-60 The Internet of Production (IoP) leverages concepts such as digital shadows, data lakes, and a World Wide Lab (WWL) to advance today’s production. Consequently, it requires a technical infrastructure that can support the agile deployment of these concepts and corresponding high-level applications, which, e.g., demand the processing of massive data in motion and at rest. As such, key research aspects are the support for low-latency control loops, concepts on scalable data stream processing, deployable information security, and semantically rich and efficient long-term storage. In particular, such an infrastructure cannot continue to be limited to machines and sensors, but additionally needs to encompass networked environments: production cells, edge computing, and location-independent cloud infrastructures. Finally, in light of the envisioned WWL, i.e., the interconnection of production sites, the technical infrastructure must be advanced to support secure and privacy-preserving industrial collaboration. To evolve today’s production sites and lay the infrastructural foundation for the IoP, we identify five broad streams of research: (1) adapting data and stream processing to heterogeneous data from distributed sources, (2) ensuring data interoperability between systems and production sites, (3) exchanging and sharing data with different stakeholders, (4) network security approaches addressing the risks of increasing interconnectivity, and (5) security architectures to enable secure and privacy-preserving industrial collaboration. With our research, we evolve the underlying infrastructure from isolated, sparsely networked production sites toward an architecture that supports high-level applications and sophisticated digital shadows while facilitating the transition toward a WWL. Cyber-physical production systems; Data streams; Industrial data processing; Industrial network security; Industrial data security; Secure industrial collaboration internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-iop-a.i.pdf Springer Interdisciplinary Excellence Accelerator Series Internet of Production: Fundamentals, Applications and Proceedings 978-3-031-44496-8 10.1007/978-3-031-44497-5_2 1 JanPennekamp AnastasiiaBelova ThomasBergs MatthiasBodenbenner AndreasBührig-Polaczek MarkusDahlmanns IkeKunze MoritzKröger SandraGeisler MartinHenze DanielLütticke BenjaminMontavon PhilippNiemietz LuciaOrtjohann MaximilianRudack Robert H.Schmitt UweVroomen KlausWehrle MichaelZeng incollection 2023_rueppel_crd-b2.ii 2023 2 8 221-246 The main objectives in production technology are quality assurance, cost reduction, and guaranteed process safety and stability. Digital shadows enable a more comprehensive understanding and monitoring of processes on shop floor level. Thus, process information becomes available between decision levels, and the aforementioned criteria regarding quality, cost, or safety can be included in control decisions for production processes. The contextual data for digital shadows typically arises from heterogeneous sources. At shop floor level, the proximity to the process requires usage of available data as well as domain knowledge. Data sources need to be selected, synchronized, and processed. Especially high-frequency data requires algorithms for intelligent distribution and efficient filtering of the main information using real-time devices and in-network computing. Real-time data is enriched by simulations, metadata from product planning, and information across the whole process chain. Well-established analytical and empirical models serve as the base for new hybrid, gray box approaches. These models are then applied to optimize production process control by maximizing the productivity under given quality and safety constraints. To store and reuse the developed models, ontologies are developed and a data lake infrastructure is utilized and constantly enlarged laying the basis for a World Wide Lab (WWL). Finally, closing the control loop requires efficient quality assessment, immediately after the process and directly on the machine. This chapter addresses works in a connected job shop to acquire data, identify and optimize models, and automate systems and their deployment in the Internet of Production (IoP). Process control; Model-based control; Data aggregation; Model identification; Model optimization internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-rueppel-iop-b2.i.pdf Springer Interdisciplinary Excellence Accelerator Series Internet of Production: Fundamentals, Applications and Proceedings 978-3-031-44496-8 10.1007/978-3-031-44497-5_7 1 Adrian KarlRüppel MuzafferAy BenediktBiernat IkeKunze MarkusLandwehr SamuelMann JanPennekamp PascalRabe Mark P.Sanders DominikScheurenberg SvenSchiller TiandongXi DirkAbel ThomasBergs ChristianBrecher UweReisgen Robert H.Schmitt KlausWehrle incollection 2023_klugewilkes_crd-b2.iv 2023 2 8 303-328 The increasing product variability and lack of skilled workers demand for autonomous, flexible production. Since assembly is considered a main cost driver and accounts for a major part of production time, research focuses on new technologies in assembly. The paradigm of Line-less Mobile Assembly Systems (LMAS) provides a solution for the future of assembly by mobilizing all resources. Thus, dynamic product routes through spatiotemporally configured assembly stations on a shop floor free of fixed obstacles are enabled. In this chapter, we present research focal points on different levels of LMAS, starting with the macroscopic level of formation planning, followed by the mesoscopic level of mobile robot control and multipurpose input devices and the microscopic level of services, such as interpreting autonomous decisions and in-network computing. We provide cross-level data and knowledge transfer through a novel ontology-based knowledge management. Overall, our work contributes to future safe and predictable human-robot collaboration in dynamic LMAS stations based on accurate online formation and motion planning of mobile robots, novel human-machine interfaces and networking technologies, as well as trustworthy AI-based decisions. Lineless mobile assembly systems (LMAS); Formation planning; Online motion planning; In-network computing; Interpretable AI; Human-machine collaboration; Ontology-based knowledge management internet-of-production https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-klugewilkes-iop-b2.iv.pdf Springer Interdisciplinary Excellence Accelerator Series Internet of Production: Fundamentals, Applications and Proceedings 978-3-031-44496-8 10.1007/978-3-031-44497-5_13 1 AlineKluge-Wilkes RalphBaier DanielGossen IkeKunze AleksandraMüller AmirShahidi DominikWolfschläger ChristianBrecher BurkhardCorves MathiasHüsing VerenaNitsch Robert H.Schmitt KlausWehrle inproceedings 2023-lorz-cired 2023 3286-3290 ven2us 27th International Conference on Electricity Distribution (CIRED 2023), Rome, Italy, June 12-15, 2023 Rome, Italy International Conference & Exhibition on Electricity Distribution (CIRED) June 12-15, 2023 10.1049/icp.2023.0864 1 TobiasLorz JohannJaeger AntigonaSelimaj ImmanuelHacker AndreasUlbig Jan-PeterHeckel ChristianBecker MarkusDahlmanns Ina BereniceFink KlausWehrle GerritErichsen MichaelSchindler RainerLuxenburger GuosongLin