Unified Data Model for Tuple-Based Trust Scheme Publication
Zusammenfassung
Trust schemes are widely used by authorities to support verifiers of electronic transactions to determine the trustworthiness of relying parties. With a tuple-based publication, in addition to the trust scheme membership, the requirements of the trust scheme are published. For this, the development and publication of a unified data model derived from existing trust schemes (e.g. eIDAS) is needed, where each requirement is explicitly represented by one tuple. The consolidation and development of this data model, which is based on nine existing trust schemes, is presented along with possible applications and added value (e.g. improved mapping of trust schemes) in the field of trust verification. The data model includes the three abstract concepts Credential, Identity, and Attributes and in total 98 concepts, which can be added to standard trust lists using ETSI TS 119 612.
- Vollständige Referenz
- BibTeX
Wagner, S., Kurowski, S. & Roßnagel, H.,
(2019).
Unified Data Model for Tuple-Based Trust Scheme Publication.
In:
Roßnagel, H., Wagner, S. & Hühnlein, D.
(Hrsg.),
Open Identity Summit 2019.
Gesellschaft für Informatik, Bonn.
(S. 131-142).
@inproceedings{mci/Wagner2019,
author = {Wagner, Sven AND Kurowski, Sebastian AND Roßnagel, Heiko},
title = {Unified Data Model for Tuple-Based Trust Scheme Publication},
booktitle = {Open Identity Summit 2019},
year = {2019},
editor = {Roßnagel, Heiko AND Wagner, Sven AND Hühnlein, Detlef} ,
pages = { 131-142 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Wagner, Sven AND Kurowski, Sebastian AND Roßnagel, Heiko},
title = {Unified Data Model for Tuple-Based Trust Scheme Publication},
booktitle = {Open Identity Summit 2019},
year = {2019},
editor = {Roßnagel, Heiko AND Wagner, Sven AND Hühnlein, Detlef} ,
pages = { 131-142 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
| Dateien | Groesse | Format | Anzeige | |
|---|---|---|---|---|
| proceedings-11.pdf | 1.881Mb | Öffnen |
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Mehr Information
ISBN: 978-3-88579-687-9
ISSN: 1617-5468
Datum: 2019
Sprache:
(en)
(en)Keywords
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