% % This file was created by the TYPO3 extension % bib % --- Timezone: CET % Creation date: 2024-03-28 % Creation time: 17-07-00 % --- Number of references % 10 % @Inproceedings { 2020_pennekamp_parameter_exchange, title = {Privacy-Preserving Production Process Parameter Exchange}, year = {2020}, month = {12}, day = {10}, pages = {510-525}, abstract = {Nowadays, collaborations between industrial companies always go hand in hand with trust issues, i.e., exchanging valuable production data entails the risk of improper use of potentially sensitive information. Therefore, companies hesitate to offer their production data, e.g., process parameters that would allow other companies to establish new production lines faster, against a quid pro quo. Nevertheless, the expected benefits of industrial collaboration, data exchanges, and the utilization of external knowledge are significant. In this paper, we introduce our Bloom filter-based Parameter Exchange (BPE), which enables companies to exchange process parameters privacy-preservingly. We demonstrate the applicability of our platform based on two distinct real-world use cases: injection molding and machine tools. We show that BPE is both scalable and deployable for different needs to foster industrial collaborations. Thereby, we reward data-providing companies with payments while preserving their valuable data and reducing the risks of data leakage.}, keywords = {secure industrial collaboration; Bloom filter; oblivious transfer; Internet of Production}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-pennekamp-parameter-exchange.pdf}, publisher = {ACM}, booktitle = {Proceedings of the 36th Annual Computer Security Applications Conference (ACSAC '20), December 7-11, 2020, Austin, TX, USA}, event_place = {Austin, TX, USA}, event_date = {December 7-11, 2020}, ISBN = {978-1-4503-8858-0/20/12}, DOI = {10.1145/3427228.3427248}, reviewed = {1}, author = {Pennekamp, Jan and Buchholz, Erik and Lockner, Yannik and Dahlmanns, Markus and Xi, Tiandong and Fey, Marcel and Brecher, Christian and Hopmann, Christian and Wehrle, Klaus} } @Inproceedings { 2020-henze-ccs-cybersecurity, title = {Poster: Cybersecurity Research and Training for Power Distribution Grids -- A Blueprint}, year = {2020}, month = {11}, day = {9}, abstract = {Mitigating cybersecurity threats in power distribution grids requires a testbed for cybersecurity, e.g., to evaluate the (physical) impact of cyberattacks, generate datasets, test and validate security approaches, as well as train technical personnel. In this paper, we present a blueprint for such a testbed that relies on network emulation and power flow computation to couple real network applications with a simulated power grid. We discuss the benefits of our approach alongside preliminary results and various use cases for cybersecurity research and training for power distribution grids.}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-henze-ccs-cybersecurity.pdf}, publisher = {ACM}, address = {New York, NY, USA}, booktitle = {Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security (CCS ’20), November 9–13, 2020, Virtual Event, USA.}, event_place = {Virtual Event, USA}, event_date = {November 9-13, 2020}, DOI = {10.1145/3372297.3420016}, reviewed = {1}, author = {Henze, Martin and Bader, Lennart and Filter, Julian and Lamberts, Olav and Ofner, Simon and van der Velde, Dennis} } @Inproceedings { 2020_matzutt_anonboot, title = {Utilizing Public Blockchains for the Sybil-Resistant Bootstrapping of Distributed Anonymity Services}, year = {2020}, month = {10}, day = {7}, pages = {531-542}, abstract = {Distributed anonymity services, such as onion routing networks or cryptocurrency tumblers, promise privacy protection without trusted third parties. While the security of these services is often well-researched, security implications of their required bootstrapping processes are usually neglected: Users either jointly conduct the anonymization themselves, or they need to rely on a set of non-colluding privacy peers. However, the typically small number of privacy peers enable single adversaries to mimic distributed services. We thus present AnonBoot, a Sybil-resistant medium to securely bootstrap distributed anonymity services via public blockchains. AnonBoot enforces that peers periodically create a small proof of work to refresh their eligibility for providing secure anonymity services. A pseudo-random, locally replicable bootstrapping process using on-chain entropy then prevents biasing the election of eligible peers. Our evaluation using Bitcoin as AnonBoot's underlying blockchain shows its feasibility to maintain a trustworthy repository of 1000 peers with only a small storage footprint while supporting arbitrarily large user bases on top of most blockchains.}, keywords = {anonymization; bootstrapping; public blockchain; Sybil attack; anonymity network; cryptocurrency tumbler; Bitcoin; Tor}, tags = {impact_digital; digital_campus}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-matzutt-anonboot.pdf}, publisher = {ACM}, booktitle = {Proceedings of the 15th ACM ASIA Conference on Computer and Communications Security (ASIACCS '20), October 5-9, 2020, Taipei, Taiwan}, event_place = {Taipei, Taiwan}, event_name = {ASIACCS 2020}, event_date = {October 5-9, 2020}, ISBN = {978-1-4503-6750-9/20/10}, DOI = {10.1145/3320269.3384729}, reviewed = {1}, author = {Matzutt, Roman and Pennekamp, Jan and Buchholz, Erik and Wehrle, Klaus} } @Article { 2020_niemietz_stamping, title = {Stamping Process Modelling in an Internet of Production}, journal = {Procedia Manufacturing}, year = {2020}, month = {7}, day = {11}, volume = {49}, pages = {61-68}, abstract = {Sharing data between companies throughout the supply chain is expected to be beneficial for product quality as well as for the economical savings in the manufacturing industry. To utilize the available data in the vision of an Internet of Production (IoP) a precise condition monitoring of manufacturing and production processes that facilitates the quantification of influences throughout the supply chain is inevitable. In this paper, we consider stamping processes in the context of an Internet of Production and the preliminaries for analytical models that utilize the ever-increasing available data. Three research objectives to cope with the amount of data and for a methodology to monitor, analyze and evaluate the influence of available data onto stamping processes have been identified: (i) State detection based on cyclic sensor signals, (ii) mapping of in- and output parameter variations onto process states, and (iii) models for edge and in-network computing approaches. After discussing state-of-the-art approaches to monitor stamping processes and the introduction of the fineblanking process as an exemplary stamping process, a research roadmap for an IoP enabling modeling framework is presented.}, note = {Proceedings of the 8th International Conference on Through-Life Engineering Service (TESConf '19), October 27-29, 2019, Cleveland, OH, USA}, keywords = {Stamping Process; Industry 4.0; Fine-blanking; Internet of production; Condition monitoring; Data analytics}, tags = {internet-of-production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-niemietz-stamping-modelling.pdf}, publisher = {Elsevier}, event_place = {Cleveland, OH, USA}, event_date = {October 27-29, 2019}, ISSN = {2351-9789}, DOI = {10.1016/j.promfg.2020.06.012}, reviewed = {1}, author = {Niemietz, Philipp and Pennekamp, Jan and Kunze, Ike and Trauth, Daniel and Wehrle, Klaus and Bergs, Thomas} } @Inproceedings { 2020-schemmel-porse, title = {Symbolic Partial-Order Execution for Testing Multi-Threaded Programs}, year = {2020}, month = {7}, tags = {symbiosys}, url = {https://arxiv.org/pdf/2005.06688.pdf}, web_url2 = {https://arxiv.org/abs/2005.06688}, booktitle = {Computer Aided Verification (CAV 2020)}, event_name = {32nd International Conference on Computer Aided Verification}, DOI = {10.1007/978-3-030-53288-8_18}, reviewed = {1}, author = {Schemmel, Daniel and B{\"u}ning, Julian and Rodr{\'i}guez, C{\'e}sar and Laprell, David and Wehrle, Klaus} } @Inproceedings { 2020_pennekamp_supply_chain_accountability, title = {Private Multi-Hop Accountability for Supply Chains}, year = {2020}, month = {6}, day = {7}, abstract = {Today's supply chains are becoming increasingly flexible in nature. While adaptability is vastly increased, these more dynamic associations necessitate more extensive data sharing among different stakeholders while simultaneously overturning previously established levels of trust. Hence, manufacturers' demand to track goods and to investigate root causes of issues across their supply chains becomes more challenging to satisfy within these now untrusted environments. Complementarily, suppliers need to keep any data irrelevant to such routine checks secret to remain competitive. To bridge the needs of contractors and suppliers in increasingly flexible supply chains, we thus propose to establish a privacy-preserving and distributed multi-hop accountability log among the involved stakeholders based on Attribute-based Encryption and backed by a blockchain. Our large-scale feasibility study is motivated by a real-world manufacturing process, i.e., a fine blanking line, and reveals only modest costs for multi-hop tracing and tracking of goods.}, keywords = {supply chain; multi-hop tracking and tracing; blockchain; attribute-based encryption; Internet of Production}, tags = {internet-of-production}, url = {https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-pennekamp-supply-chain-privacy.pdf}, publisher = {IEEE}, booktitle = {Proceedings of the 2020 IEEE International Conference on Communications Workshops (ICC Workshops '20), 1st Workshop on Blockchain for IoT and Cyber-Physical Systems (BIoTCPS '20), June 7-11, 2020, Dublin, Ireland}, event_place = {Dublin, Ireland}, event_date = {June 7-11, 2020}, ISBN = {978-1-7281-7440-2}, ISSN = {2474-9133}, DOI = {10.1109/ICCWorkshops49005.2020.9145100}, reviewed = {1}, author = {Pennekamp, Jan and Bader, Lennart and Matzutt, Roman and Niemietz, Philipp and Trauth, Daniel and Henze, Martin and Bergs, Thomas and Wehrle, Klaus} } @Article { 2020_gleim_factDAG, title = {FactDAG: Formalizing Data Interoperability in an Internet of Production}, journal = {IEEE Internet of Things Journal}, year = {2020}, month = {4}, day = {14}, volume = {7}, number = {4}, pages = {3243-3253}, abstract = {In the production industry, the volume, variety and velocity of data as well as the number of deployed protocols increase exponentially due to the influences of IoT advances. While hundreds of isolated solutions exist to utilize this data, e.g., optimizing processes or monitoring machine conditions, the lack of a unified data handling and exchange mechanism hinders the implementation of approaches to improve the quality of decisions and processes in such an interconnected environment. The vision of an Internet of Production promises the establishment of a Worldwide Lab, where data from every process in the network can be utilized, even interorganizational and across domains. While numerous existing approaches consider interoperability from an interface and communication system perspective, fundamental questions of data and information interoperability remain insufficiently addressed. In this paper, we identify ten key issues, derived from three distinctive real-world use cases, that hinder large-scale data interoperability for industrial processes. Based on these issues we derive a set of five key requirements for future (IoT) data layers, building upon the FAIR data principles. We propose to address them by creating FactDAG, a conceptual data layer model for maintaining a provenance-based, directed acyclic graph of facts, inspired by successful distributed version-control and collaboration systems. Eventually, such a standardization should greatly shape the future of interoperability in an interconnected production industry.}, keywords = {Data Management; Data Versioning; Interoperability; Industrial Internet of Things; Worldwide Lab}, tags = {internet-of-production}, url = {https://comsys.rwth-aachen.de/fileadmin/papers/2020/2020-gleim-iotj-iop-interoperability.pdf}, publisher = {IEEE}, ISSN = {2327-4662}, DOI = {10.1109/JIOT.2020.2966402}, reviewed = {1}, author = {Gleim, Lars and Pennekamp, Jan and Liebenberg, Martin and Buchsbaum, Melanie and Niemietz, Philipp and Knape, Simon and Epple, Alexander and Storms, Simon and Trauth, Daniel and Bergs, Thomas and Brecher, Christian and Decker, Stefan and Lakemeyer, Gerhard and Wehrle, Klaus} } @Article { 2020_mann_welding_layers, title = {Connected, digitalized welding production — Secure, ubiquitous utilization of data across process layers}, journal = {Advanced Structured Materials}, year = {2020}, month = {4}, day = {1}, volume = {125}, pages = {101-118}, abstract = {A connected, digitalized welding production unlocks vast and dynamic potentials: from improving state of the art welding to new business models in production. For this reason, offering frameworks, which are capable of addressing multiple layers of applications on the one hand and providing means of data security and privacy for ubiquitous dataflows on the other hand, is an important step to enable the envisioned advances. In this context, welding production has been introduced from the perspective of interlaced process layers connecting information sources across various entities. Each layer has its own distinct challenges from both a process view and a data perspective. Besides, investigating each layer promises to reveal insight into (currently unknown) process interconnections. This approach has been substantiated by methods for data security and privacy to draw a line between secure handling of data and the need of trustworthy dealing with sensitive data among different parties and therefore partners. In conclusion, the welding production has to develop itself from an accumulation of local and isolated data sources towards a secure industrial collaboration in an Internet of Production.}, note = {Proceedings of the 1st International Conference on Advanced Joining Processes (AJP '19)}, keywords = {Welding Production; Industrie 4.0; Internet of Production; Data Security; Data Privacy}, tags = {Internet-of-Production}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-mann-welding-layers.pdf}, publisher = {Springer}, event_place = {Ponta Delgada, Azores, Portugal}, event_date = {October 24-25, 2019}, ISBN = {978-981-15-2956-6}, ISSN = {1869-8433}, DOI = {10.1007/978-981-15-2957-3_8}, reviewed = {1}, author = {Mann, Samuel and Pennekamp, Jan and Brockhoff, Tobias and Farhang, Anahita and Pourbafrani, Mahsa and Oster, Lukas and Uysal, Merih Seran and Sharma, Rahul and Reisgen, Uwe and Wehrle, Klaus and van der Aalst, Wil} } @Inproceedings { 2020-kosek-tcp-conformance, title = {MUST, SHOULD, DON'T CARE: TCP Conformance in the Wild}, year = {2020}, month = {3}, day = {30}, tags = {maki}, url = {https://www.comsys.rwth-aachen.de/fileadmin/papers/2020/2020-kosek-tcp-conformance-v2.pdf}, web_url2 = {https://arxiv.org/abs/2002.05400}, publisher = {Springer}, booktitle = {Proceedings of the Passive and Active Measurement Conference (PAM '20)}, event_place = {Eugene, Oregon, USA}, event_name = {Passive and Active Measurement Conference (PAM 2020)}, event_date = {30.03.2020 - 31.03.2020}, language = {en}, DOI = {https://doi.org/10.1007/978-3-030-44081-7_8}, reviewed = {1}, author = {Kosek, Mike and Bl{\"o}cher, Leo and R{\"u}th, Jan and Zimmermann, Torsten and Hohlfeld, Oliver} } @Article { 2020-wehrle-digitalshadows, title = {Mit ''Digitalen Schatten'' Daten verdichten und darstellen : Der Exzellenzcluster ''Internet der Produktion'' forscht {\"u}ber die Produktionstechnik hinaus}, journal = {Der Profilbereich ''Information \& Communication Technology''}, year = {2020}, ISSN = {0179-079X}, DOI = {10.18154/RWTH-2021-02496}, author = {Jarke, Matthias and van der Aalst, Wil and Brecher, Christian and Brockmann, Matthias and Koren, Istv{\'a}n and Lakemeyer, Gerhard and Rumpe, Bernhard and Schuh, G{\"u}nther and Wehrle, Klaus and Ziefle, Martina} }