Abstract
Originalsprache | englisch |
---|---|
Titel | 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) |
Herausgeber (Verlag) | IEEE Computer Society |
Seiten | 1157-1163 |
ISBN (elektronisch) | 978-1-5386-4388-4 |
ISBN (Print) | 978-1-5386-4389-1 |
DOIs | |
Publikationsstatus | Veröffentlicht - 6 Sep 2018 |
Veranstaltung | 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 - New York, USA / Vereinigte Staaten Dauer: 31 Jul 2018 → 3 Aug 2018 |
Konferenz
Konferenz | 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 |
---|---|
Land | USA / Vereinigte Staaten |
Ort | New York |
Zeitraum | 31/07/18 → 3/08/18 |
Fingerprint
Schlagwörter
Dies zitieren
Towards Domain-Specific and Privacy-Preserving Qualified eID in a User-Centric Identity Model. / Lenz, Thomas; Krnjic, Vesna.
2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE Computer Society, 2018. S. 1157-1163.Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Forschung › Begutachtung
}
TY - GEN
T1 - Towards Domain-Specific and Privacy-Preserving Qualified eID in a User-Centric Identity Model
AU - Lenz, Thomas
AU - Krnjic, Vesna
PY - 2018/9/6
Y1 - 2018/9/6
N2 - Unique and qualified identification is essential in numerous security-critical areas, like eGovernment, or eBusiness. Therefore, many countries have already deployed eID solutions to confirm identity information of entities and to increase trust into the identity information. Many of these confirmation solutions only support an all-or-nothing disclosure, which means that selective disclosure of single attributes is not possible. Some other work has dealt with this privacy issue by using anonymous credentials or malleable signatures. However, all of these solutions lacks in flexible generation of qualified and provable pseudonyms that based on confirmed eID information. In this paper, we propose an advanced and lightweight model for user-centric and qualified identity information that facilitates selective disclosure and domain-specific altering of single identity attributes in order to protect the citizen's privacy. We illustrate the practical applicability of our model by implementing all components as prototype applications. Finally, we evaluate our model and compare it with other approaches for selective disclosure.
AB - Unique and qualified identification is essential in numerous security-critical areas, like eGovernment, or eBusiness. Therefore, many countries have already deployed eID solutions to confirm identity information of entities and to increase trust into the identity information. Many of these confirmation solutions only support an all-or-nothing disclosure, which means that selective disclosure of single attributes is not possible. Some other work has dealt with this privacy issue by using anonymous credentials or malleable signatures. However, all of these solutions lacks in flexible generation of qualified and provable pseudonyms that based on confirmed eID information. In this paper, we propose an advanced and lightweight model for user-centric and qualified identity information that facilitates selective disclosure and domain-specific altering of single identity attributes in order to protect the citizen's privacy. We illustrate the practical applicability of our model by implementing all components as prototype applications. Finally, we evaluate our model and compare it with other approaches for selective disclosure.
KW - privacy
KW - Digital signatures
KW - Smart devices
KW - Cryptography
KW - Stakeholders
KW - authentication
KW - Data models
U2 - 10.1109/TrustCom/BigDataSE.2018.00160
DO - 10.1109/TrustCom/BigDataSE.2018.00160
M3 - Conference contribution
SN - 978-1-5386-4389-1
SP - 1157
EP - 1163
BT - 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
PB - IEEE Computer Society
ER -