Blockchain-based Learning Credential Verification System with Recipient Privacy Control

Abstract

Various forms of learning credentials play an important role in society. For example, a degree certificate is usually required to apply for many jobs. Currently, paper-based learning credentials such as diploma or degree certificates are still widely used. However, proof of such credentials' authenticity has become increasingly more difficult in recently years due to availability of low-cost desktop publishing tools. Recently, a blockchain-based digital certificate issuing and verification system has been proposed to address these problems. However, existing blockchain-based certification verification solutions have a few shortcomings in common. One of them is the lack of mechanism to control the amount of information and anonymity exposed during the verification process. This paper proposed a blockchain-based learning credential verification system, where a credential recipient can control the amount of credential-related information to be exposed during the verification process. The proposed solution makes use of a Merkle tree to encode causal relationship among pieces of information the credential is composed of. The abstract data model built on top of the binary Merkle tree has been proposed so that a recipient can choose to disclose part of the credential information, including the recipient profile. This means it is possible for credential verification to be performed anonymously. This can be achieved without increasing blockchain transaction cost and complexity. Example of use case scenarios that require such anonymous verification are described.