Confidentiality Preserving Data Sharing for Life Cycle Assessment in Process Industries

Hansani Wanni Arachchige Dona*, Udayanto Dwi Atmojo*, Valeriy Vyatkin*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)
4 Downloads (Pure)

Abstract

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.

Original languageEnglish
Title of host publication2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation, ETFA 2024
EditorsTullio Facchinetti, Angelo Cenedese, Lucia Lo Bello, Stefano Vitturi, Thilo Sauter, Federico Tramarin
PublisherIEEE
Number of pages4
ISBN (Electronic)979-8-3503-6123-0
DOIs
Publication statusPublished - 2024
MoE publication typeA4 Conference publication
EventIEEE International Conference on Emerging Technologies and Factory Automation - Padova, Italy
Duration: 10 Sept 202413 Sept 2024

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Conference

ConferenceIEEE International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA
Country/TerritoryItaly
CityPadova
Period10/09/202413/09/2024

Keywords

  • Confidentiality
  • Data spaces
  • Lifecycle Assessment (LCA)
  • Privacy
  • Secure MultiParty Computation (SMPC)

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