Matching Metadata on Blockchain for Self-Sovereign Identity

Self-Sovereign Identity (SSI) is a privacy-preserving identity paradigm where users own and manage their digital identities. SSI is also referred to as blockchain identity, as it is commonly implemented using distributed ledger technologies. In this work, we describe the problem of schema matching on blockchain-based SSI implementations, systematically review the literature for tools that attack this problem, introduce a novel solution, and empirically compare it with the works reported from our literature review. Our solution uses pre-trained word vectors to find semantic similarities between user queries and schemas on the blockchain. Experimental evaluation shows that it outperforms existing solutions regarding queries that approach natural language.