% % This file was created by the TYPO3 extension % bib % --- Timezone: CEST % Creation date: 2024-04-23 % Creation time: 14-17-00 % --- Number of references % 11 % @Inproceedings { 2023_matzutt_street_problems, title = {Poster: Accountable Processing of Reported Street Problems}, year = {2023}, month = {11}, day = {27}, pages = {3591-3593}, abstract = {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.}, keywords = {street problems; accountability; consortium blockchain; privacy}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-matzutt-street-problems.pdf}, publisher = {ACM}, booktitle = {Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS ’23), November 26-30, 2023, Copenhagen, Denmark}, event_place = {Copenhagen, Denmark}, event_date = {November 26-30, 2023}, ISBN = {979-8-4007-0050-7/23/11}, DOI = {10.1145/3576915.3624367}, reviewed = {1}, author = {Matzutt, Roman and Pennekamp, Jan and Wehrle, Klaus} } @Article { 2023_pennekamp_purchase_inquiries, title = {Offering Two-Way Privacy for Evolved Purchase Inquiries}, journal = {ACM Transactions on Internet Technology}, year = {2023}, month = {11}, day = {17}, volume = {23}, number = {4}, abstract = {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.}, keywords = {bootstrapping procurement; secure industrial collaboration; private set intersection; homomorphic encryption; Internet of Production}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-purchase-inquiries.pdf}, publisher = {ACM}, ISSN = {1533-5399}, DOI = {10.1145/3599968}, reviewed = {1}, author = {Pennekamp, Jan and Dahlmanns, Markus and Fuhrmann, Frederik and Heutmann, Timo and Kreppein, Alexander and Grunert, Dennis and Lange, Christoph and Schmitt, Robert H. and Wehrle, Klaus} } @Inproceedings { 2023_bader_reputation-systems, title = {Reputation Systems for Supply Chains: The Challenge of Achieving Privacy Preservation}, year = {2023}, month = {11}, abstract = {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.}, note = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST)}, keywords = {SCM; confidentiality; anonymity; voter; votee; FHE}, tags = {internet-of-production}, url = {https://jpennekamp.de/wp-content/papercite-data/pdf/bpt+23.pdf}, publisher = {Springer}, booktitle = {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}, event_place = {Melbourne, VIC, Australia}, event_date = {November 14-17, 2023}, state = {accepted}, ISSN = {1867-8211}, reviewed = {1}, author = {Bader, Lennart and Pennekamp, Jan and Thevaraj, Emildeon and Spi{\ss}, Maria and Kanhere, Salil S. and Wehrle, Klaus} } @Article { 2023_hauser_technical-documentation, title = {Tool: Automatically Extracting Hardware Descriptions from PDF Technical Documentation}, journal = {Journal of Systems Research}, year = {2023}, month = {10}, day = {31}, volume = {3}, number = {1}, abstract = {The ever-increasing variety of microcontrollers aggravates the challenge of porting embedded software to new devices through much manual work, whereas code generators can be used only in special cases. Moreover, only little technical documentation for these devices is available in machine-readable formats that could facilitate automating porting efforts. Instead, the bulk of documentation comes as print-oriented PDFs. We hence identify a strong need for a processor to access the PDFs and extract their data with a high quality to improve the code generation for embedded software. In this paper, we design and implement a modular processor for extracting detailed datasets from PDF files containing technical documentation using deterministic table processing for thousands of microcontrollers. Namely, we systematically extract device identifiers, interrupt tables, package and pinouts, pin functions, and register maps. In our evaluation, we compare the documentation from STMicro against existing machine-readable sources. Our results show that our processor matches 96.5 \% of almost 6 million reference data points, and we further discuss identified issues in both sources. Hence, our tool yields very accurate data with only limited manual effort and can enable and enhance a significant amount of existing and new code generation use cases in the embedded software domain that are currently limited by a lack of machine-readable data sources.}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-hauser-technical-documents.pdf}, publisher = {eScholarship Publishing}, ISSN = {2770-5501}, DOI = {10.5070/SR33162446}, reviewed = {1}, author = {Hauser, Niklas and Pennekamp, Jan} } @Article { 2023_lamberts_metrics-sok, title = {SoK: Evaluations in Industrial Intrusion Detection Research}, journal = {Journal of Systems Research}, year = {2023}, month = {10}, day = {31}, volume = {3}, number = {1}, abstract = {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.}, tags = {internet-of-production, rfc}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-lamberts-metrics-sok.pdf}, publisher = {eScholarship Publishing}, ISSN = {2770-5501}, DOI = {10.5070/SR33162445}, reviewed = {1}, author = {Lamberts, Olav and Wolsing, Konrad and Wagner, Eric and Pennekamp, Jan and Bauer, Jan and Wehrle, Klaus and Henze, Martin} } @Inproceedings { 2023-wolsing-xluuvlab, title = {XLab-UUV – A Virtual Testbed for Extra-Large Uncrewed Underwater Vehicles}, year = {2023}, month = {10}, abstract = {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.}, keywords = {Maritime Simulation Environment, XLUUV, Cyber Range, Autonomous Shipping, Operational Technology}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-wolsing-xluuvlab.pdf}, publisher = {IEEE}, booktitle = {1st IEEE LCN Workshop on Maritime Communication and Security (MarCaS)}, event_place = {Daytona Beach, Florida, USA}, event_name = {1st IEEE LCN Workshop on Maritime Communication and Security (MarCaS)}, event_date = {Oktober 1-5, 2023}, state = {accepted}, language = {en}, DOI = {10.1109/LCN58197.2023.10223405}, reviewed = {1}, author = {Wolsing, Konrad and Saillard, Antoine and Padilla, Elmar and Bauer, Jan} } @Inproceedings { 2023_wolsing_ensemble, title = {One IDS is not Enough! Exploring Ensemble Learning for Industrial Intrusion Detection}, year = {2023}, month = {9}, day = {25}, volume = {14345}, pages = {102-122}, abstract = {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.}, note = {Lecture Notes in Computer Science (LNCS), Volume 14345}, keywords = {Intrusion Detection; Ensemble Learning; ICS}, tags = {internet-of-production, rfc}, url = {https://jpennekamp.de/wp-content/papercite-data/pdf/wkw+23.pdf}, publisher = {Springer}, booktitle = {Proceedings of the 28th European Symposium on Research in Computer Security (ESORICS '23), September 25-29, 2023, The Hague, The Netherlands}, event_place = {The Hague, The Netherlands}, event_name = {28th European Symposium on Research in Computer Security (ESORICS '23)}, event_date = {September 25-29, 2023}, ISBN = {978-3-031-51475-3}, ISSN = {0302-9743}, DOI = {10.1007/978-3-031-51476-0_6}, reviewed = {1}, author = {Wolsing, Konrad and Kus, Dominik and Wagner, Eric and Pennekamp, Jan and Wehrle, Klaus and Henze, Martin} } @Inproceedings { 2023_bodenbenner_fairsensor, title = {FAIR Sensor Ecosystem: Long-Term (Re-)Usability of FAIR Sensor Data through Contextualization}, year = {2023}, month = {7}, day = {20}, abstract = {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.}, keywords = {FAIR Data; Cyber-Physical Systems; Data Management; Data Contextualization; Internet of Production}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-bodenbenner-fair-ecosystem.pdf}, publisher = {IEEE}, booktitle = {Proceedings of the 21th IEEE International Conference on Industrial Informatics (INDIN '23), July 17-20, 2023, Lemgo, Germany}, event_place = {Lemgo, Germany}, event_date = {July 17-20, 2023}, ISBN = {978-1-6654-9313-0}, ISSN = {2378-363X}, DOI = {10.1109/INDIN51400.2023.10218149}, reviewed = {1}, author = {Bodenbenner, Matthias and Pennekamp, Jan and Montavon, Benjamin and Wehrle, Klaus and Schmitt, Robert H.} } @Inproceedings { 2023_pennekamp_benchmarking_comparison, title = {Designing Secure and Privacy-Preserving Information Systems for Industry Benchmarking}, year = {2023}, month = {6}, day = {15}, volume = {13901}, pages = {489-505}, abstract = {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.}, note = {Lecture Notes in Computer Science (LNCS), Volume 13901}, keywords = {real-world computing; trusted execution environments; homomorphic encryption; key performance indicators; benchmarking}, tags = {internet-of-production}, url = {https://jpennekamp.de/wp-content/papercite-data/pdf/plv+23.pdf}, publisher = {Springer}, booktitle = {Proceedings of the 35th International Conference on Advanced Information Systems Engineering (CAiSE '23), June 12-16, 2023, Zaragoza, Spain}, event_place = {Zaragoza, Spain}, event_name = {35th International Conference on Advanced Information Systems Engineering (CAiSE '23)}, event_date = {June 12-16, 2023}, ISBN = {978-3-031-34559-3}, ISSN = {0302-9743}, DOI = {10.1007/978-3-031-34560-9_29}, reviewed = {1}, author = {Pennekamp, Jan and Lohm{\"o}ller, Johannes and Vlad, Eduard and Loos, Joscha and Rodemann, Niklas and Sapel, Patrick and Fink, Ina Berenice and Schmitz, Seth and Hopmann, Christian and Jarke, Matthias and Schuh, G{\"u}nther and Wehrle, Klaus and Henze, Martin} } @Incollection { 2023_pennekamp_crd-a.i, title = {Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead}, year = {2023}, month = {2}, day = {8}, pages = {35-60}, abstract = {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.}, keywords = {Cyber-physical production systems; Data streams; Industrial data processing; Industrial network security; Industrial data security; Secure industrial collaboration}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-pennekamp-iop-a.i.pdf}, publisher = {Springer}, series = {Interdisciplinary Excellence Accelerator Series}, booktitle = {Internet of Production: Fundamentals, Applications and Proceedings}, ISBN = {978-3-031-44496-8}, DOI = {10.1007/978-3-031-44497-5_2}, reviewed = {1}, author = {Pennekamp, Jan and Belova, Anastasiia and Bergs, Thomas and Bodenbenner, Matthias and B{\"u}hrig-Polaczek, Andreas and Dahlmanns, Markus and Kunze, Ike and Kr{\"o}ger, Moritz and Geisler, Sandra and Henze, Martin and L{\"u}tticke, Daniel and Montavon, Benjamin and Niemietz, Philipp and Ortjohann, Lucia and Rudack, Maximilian and Schmitt, Robert H. and Vroomen, Uwe and Wehrle, Klaus and Zeng, Michael} } @Incollection { 2023_rueppel_crd-b2.ii, title = {Model-Based Controlling Approaches for Manufacturing Processes}, year = {2023}, month = {2}, day = {8}, pages = {221-246}, abstract = {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).}, keywords = {Process control; Model-based control; Data aggregation; Model identification; Model optimization}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2023/2023-rueppel-iop-b2.i.pdf}, publisher = {Springer}, series = {Interdisciplinary Excellence Accelerator Series}, booktitle = {Internet of Production: Fundamentals, Applications and Proceedings}, ISBN = {978-3-031-44496-8}, DOI = {10.1007/978-3-031-44497-5_7}, reviewed = {1}, author = {R{\"u}ppel, Adrian Karl and Ay, Muzaffer and Biernat, Benedikt and Kunze, Ike and Landwehr, Markus and Mann, Samuel and Pennekamp, Jan and Rabe, Pascal and Sanders, Mark P. and Scheurenberg, Dominik and Schiller, Sven and Xi, Tiandong and Abel, Dirk and Bergs, Thomas and Brecher, Christian and Reisgen, Uwe and Schmitt, Robert H. and Wehrle, Klaus} }