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Trust Me If You Can: Trusted Transformation Between (JSON) Schemas to Support Global Authentication of Education Credentials
- Source :
- Proceedings of the 36th IFIP TC 11 International Conference on ICT Systems Security and Privacy Protection (IFIP SEC 2021)/IFIP Advances in Information and Communication Technology, vol. 625, 2021, 19-35
- Publication Year :
- 2021
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Abstract
- Recruiters and institutions around the world struggle with the verification of diplomas issued in a diverse and global education setting. Firstly, it is a nontrivial problem to identify bogus institutions selling education credentials. While institutions are often accredited by qualified authorities on a regional level, there is no global authority fulfilling this task. Secondly, many different data schemas are used to encode education credentials, which represents a considerable challenge to automated processing. Consequently, significant manual effort is required to verify credentials. In this paper, we tackle these challenges by introducing a decentralized and open system to automatically verify the legitimacy of issuers and interpret credentials in unknown schemas. We do so by enabling participants to publish transformation information, which enables verifiers to transform credentials into their preferred schema. Due to the lack of a global root of trust, we utilize a distributed ledger to build a decentralized web of trust, which verifiers can query to gather information on the trustworthiness of issuing institutions and to establish trust in transformation information. Going beyond diploma fraud, our system can be generalized to tackle the generalized problem for other domains lacking a root of trust and agreements on data schemas.<br />Comment: 16 pages, 4 figures
- Subjects :
- Computer Science - Computers and Society
Subjects
Details
- Database :
- arXiv
- Journal :
- Proceedings of the 36th IFIP TC 11 International Conference on ICT Systems Security and Privacy Protection (IFIP SEC 2021)/IFIP Advances in Information and Communication Technology, vol. 625, 2021, 19-35
- Publication Type :
- Report
- Accession number :
- edsarx.2106.12793
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1007/978-3-030-78120-0_2