Abstract
Background and Purpose:
The paper and pulp industry faces significant environmental challenges, including air pollution, greenhouse gas emissions, and wastewater discharge, necessitating sustainable operations. Regulatory bodies impose stringent measures to mitigate these impacts, compelling the industry to adopt sustainable practices and technologies. Life Cycle Assessment (LCA) models are crucial for evaluating environmental impacts and aiding sustainable manufacturing decisions. However, organisations prioritise the confidentiality of sensitive data, hindering collaborative LCA efforts. This study addresses the need for enhancing data confidentiality, tamper-proof data transfer, and ensuring data sovereignty using Secure Multi-Party Computation (SMPC) and data spaces.
Methods:
The study involves the development of a data space for sharing information among organisations using a standardised data model. Open-source components provided by the International Data Spaces Association (IDSA) have been utilised in creating this data space. The fundamental solution comprises a broker responsible for holding metadata of the published data, a certification authority to verify each organisation, an access management service, and data space connectors to link the data resources of organisations with the data space. The transfer of data is secured using Secure Socket Layer (SSL). Additionally, SMPC algorithms need to be implemented atop the data space to compute functions over inputs while maintaining the privacy of those inputs. The calculated results will be verified using zero-knowledge proofs (ZKP).
Results/Hypothesis:
The integration of SMPC and data spaces within a LCA platform will significantly enhance data confidentiality and data sovereignty, enabling more accurate and collaborative LCA calculations without exposing sensitive information. By leveraging cryptographic techniques, such as ZKP and SSL, the proposed platform will ensure trust in computations and the security of data transfer. This will promote sustainable practices across the supply chain by facilitating tamper-proof data sharing while preserving the privacy of proprietary data.
Conclusions:
The proposed framework for privacy-preserving LCA in the paper and pulp industry enhances sustainability by facilitating accurate LCA calculations without necessitating organisations to share their sensitive data with one another. This ensures that all participants can contribute their data transparently, supporting accurate and transparent LCA assessments while safeguarding sensitive information within the value chain.
The paper and pulp industry faces significant environmental challenges, including air pollution, greenhouse gas emissions, and wastewater discharge, necessitating sustainable operations. Regulatory bodies impose stringent measures to mitigate these impacts, compelling the industry to adopt sustainable practices and technologies. Life Cycle Assessment (LCA) models are crucial for evaluating environmental impacts and aiding sustainable manufacturing decisions. However, organisations prioritise the confidentiality of sensitive data, hindering collaborative LCA efforts. This study addresses the need for enhancing data confidentiality, tamper-proof data transfer, and ensuring data sovereignty using Secure Multi-Party Computation (SMPC) and data spaces.
Methods:
The study involves the development of a data space for sharing information among organisations using a standardised data model. Open-source components provided by the International Data Spaces Association (IDSA) have been utilised in creating this data space. The fundamental solution comprises a broker responsible for holding metadata of the published data, a certification authority to verify each organisation, an access management service, and data space connectors to link the data resources of organisations with the data space. The transfer of data is secured using Secure Socket Layer (SSL). Additionally, SMPC algorithms need to be implemented atop the data space to compute functions over inputs while maintaining the privacy of those inputs. The calculated results will be verified using zero-knowledge proofs (ZKP).
Results/Hypothesis:
The integration of SMPC and data spaces within a LCA platform will significantly enhance data confidentiality and data sovereignty, enabling more accurate and collaborative LCA calculations without exposing sensitive information. By leveraging cryptographic techniques, such as ZKP and SSL, the proposed platform will ensure trust in computations and the security of data transfer. This will promote sustainable practices across the supply chain by facilitating tamper-proof data sharing while preserving the privacy of proprietary data.
Conclusions:
The proposed framework for privacy-preserving LCA in the paper and pulp industry enhances sustainability by facilitating accurate LCA calculations without necessitating organisations to share their sensitive data with one another. This ensures that all participants can contribute their data transparently, supporting accurate and transparent LCA assessments while safeguarding sensitive information within the value chain.
| Original language | English |
|---|---|
| Pages | 19-20 |
| Number of pages | 2 |
| Publication status | Published - 2024 |
| MoE publication type | Not Eligible |
| Event | SETAC Europe LCA Symposium - Chalmers Conference Centre Gothenburg, Gothenburg, Sweden Duration: 21 Oct 2024 → 23 Oct 2024 Conference number: 26 https://www.setac.org/discover-events/topical-events/setac-europe-26th-lca-symposium.html |
Conference
| Conference | SETAC Europe LCA Symposium |
|---|---|
| Country/Territory | Sweden |
| City | Gothenburg |
| Period | 21/10/2024 → 23/10/2024 |
| Internet address |
