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Confidentiality Preserving Data Sharing for Life Cycle Assessment in Process Industries
Aalto University, Department of Electrical Engineering and Automation, Espoo, Finland.
Aalto University, Department of Electrical Engineering and Automation, Espoo, Finland.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Aalto University, Department of Electrical Engineering and Automation, Espoo, Finland.ORCID iD: 0000-0002-9315-9920
2024 (English)In: 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation - ETFA 2024 / [ed] Tullio Facchinetti, Angelo Cenedese, Lucia Lo Bello, Stefano Vitturi, Thilo Sauter, Federico Tramarin, IEEE, 2024Conference paper, Published paper (Refereed)
Abstract [en]

The pulp and paper industry faces significant en-vironmental challenges, such as air pollution, greenhouse gas emissions, and wastewater discharge, requiring smarter and more sustainable operations. Regulatory bodies are imposing stringent measures to mitigate these impacts, prompting the industry to adopt sustainable practices and technologies. Life Cycle Assessment (LCA) models are crucial in this effort, pro-viding a comprehensive evaluation of environmental impacts and aiding decision making for sustainable manufacturing. However, organisations prioritise the confidentiality of their sensitive data, which can hinder collaborative efforts and LCA calculations. This paper addresses organisational requirements for improving confidentiality, tamper-proof data transfer, and ensuring data sovereignty. The ongoing proof-of-concept introduces a novel approach in LCA, employing Secure Multiparty Computation (SMPC) and data spaces to enable confidentiality-preserving LCA. Our solution ensures data sovereignty and accurate LCA calculations, promoting sustainable practices across the value chain. This paper lays the foundation for a collaborative data platform that meets the critical needs of confidentiality, security, and sustainability in the process manufacturing industry.

Place, publisher, year, edition, pages
IEEE, 2024.
Keywords [en]
Confidentiality, Data spaces, Lifecycle Assessment (LCA), Privacy, Secure MultiParty Computation (SMPC)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-110689DOI: 10.1109/ETFA61755.2024.10710738Scopus ID: 2-s2.0-85207839198OAI: oai:DiVA.org:ltu-110689DiVA, id: diva2:1912582
Conference
IEEE International Conference on Emerging Technologies and Factory Automation (EFTA 2024), Padova, Italy, September 10-13, 2024
Note

Funder: Horison Europe  (8168/31/2022); Business Finland (8168/31/2022); 

ISBN for host publication: 979-8-3503-6123-0;

Available from: 2024-11-12 Created: 2024-11-12 Last updated: 2024-11-12Bibliographically approved

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Vyatkin, Valeriy

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