This file was created by the TYPO3 extension bib --- Timezone: CEST Creation date: 2023-06-08 Creation time: 09-46-58 --- Number of references 6 inproceedings 2023_pennekamp_benchmarking_comparison Designing Secure and Privacy-Preserving Information Systems for Industry Benchmarking 2023 6 15 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 accepted 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 article 2023-circres-wu-comp-ecosystem Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk 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 Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead 2023 2 8 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 Internet of Production: Fundamentals, Applications and Proceedings 978-3-030-98062-7 10.1007/978-3-030-98062-7_2-1 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 Model-Based Controlling Approaches for Manufacturing Processes 2023 2 8 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 Internet of Production: Fundamentals, Applications and Proceedings 978-3-030-98062-7 10.1007/978-3-030-98062-7_7-1 1 Adrian KarlRüppel MuzafferAy BenediktBiernat IkeKunze MarkusLandwehr SamuelMann JanPennekamp PascalRabe Mark P.Sanders DominikScheurenberg SvenSchiller TiandongXi DirkAbel ThomasBergs ChristianBrecher UweReisgen Robert H.Schmitt KlausWehrle article 2023_pennekamp_purchase_inquiries Offering Two-Way Privacy for Evolved Purchase Inquiries ACM Transactions on Internet Technology 2023 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 accepted 1533-5399 10.1145/3599968 1 JanPennekamp MarkusDahlmanns FrederikFuhrmann TimoHeutmann AlexanderKreppein DennisGrunert ChristophLange Robert H.Schmitt KlausWehrle inproceedings 2023-lorz-cired Interconnected Grid Protection Systems - Reference Grid For Testing An Adaptive Protection Scheme 2023 ven2us Proceedings of the International Conference & Exhibition on Electricity Distribution (CIRED) 2023 Rome International Conference & Exhibition on Electricity Distribution (CIRED) 12-15 June 2023 1 TobiasLorz JohannJaeger AntigonaSelimaj ImmanuelHacker AndreasUlbig Jan-PeterHeckel ChristianBecker MarkusDahlmanns Ina BereniceFink KlausWehrle GerritErichsen MichaelSchindler RainerLuxenburger GuosongLin