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dc.contributor.authorBrucker, AD
dc.contributor.authorYalman, S
dc.date.accessioned2021-10-18T10:05:34Z
dc.date.issued2022-01-01
dc.description.abstractThe environmental impact of products is an important factor in buying decisions of customers and it is also an increasing concern of law makers. Hence, companies are interested in determining the ecological footprint of their products. Life-cycle assessment (LCA) is a standardized method for computing the ecological footprint of a product. Today, LCA is usually not computed in real-time and neither is LCA using actual sensor data: in contrast it is computed “offline” using “historic” values based on exemplary measurements. With the rise of the Internet of Things (IoT), LCA computations can be based on actual production processes. While an LCA based on actual sensor data is desirable from an ecological perspective, it also can reveal trade secrets, e.g., details about production processes or business relationships. In this paper, we present an approach, using secure multi-party computation, to enable the confidential data sharing required for an LCA computation using sensor data.en_GB
dc.description.sponsorshipTurkish Ministry of National Educationen_GB
dc.identifier.citationVol. 436, pp. 434-446|en_GB
dc.identifier.doi10.1007/978-3-030-94343-1_33
dc.identifier.urihttp://hdl.handle.net/10871/127492
dc.language.isoenen_GB
dc.publisherSpringer Verlagen_GB
dc.relation.urlhttps://git.logicalhacking.com/PrivacyPreservingLCA/ConfidentialLCAen_GB
dc.rights.embargoreasonUnder embargo until 1 January 2023 in compliance with publisher policyen_GB
dc.rights© Springer Nature Switzerland AG 2022
dc.subjectLife-Cycle Assessmenten_GB
dc.subjectLCAen_GB
dc.subjectConfidential Computationen_GB
dc.subjectSecure Multi-Party Computationen_GB
dc.subjectSMPCen_GB
dc.titleConfidentiality Enhanced Life-Cycle Assessmenten_GB
dc.typeConference paperen_GB
dc.date.available2021-10-18T10:05:34Z
dc.contributor.editorMarrella, Aen_GB
dc.contributor.editorWeber, Ben_GB
dc.identifier.issn1865-1348
exeter.place-of-publicationHeidelbergen_GB
dc.descriptionThis is the author accepted manuscript. The final version is available from Springer via the DOI in this recorden_GB
dc.descriptionAvailability. Our prototype is available at https://git.logicalhacking. com/PrivacyPreservingLCA/ConfidentialLCA under an Apache license (SPDX-License-Identifier: Apache-2.0).en_GB
dc.descriptionBusiness Process Management Workshops: BPM 2021 International Workshops, Rome, Italy, 6–10 September 2021en_GB
dc.identifier.journalLecture Notes in Business Information Processingen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2021-10-18
rioxxterms.typeConference Paper/Proceeding/Abstracten_GB
refterms.dateFCD2021-10-18T10:03:36Z
refterms.versionFCDAM
refterms.panelBen_GB


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