We have completed yet another milestone in our roadmap today by releasing the claim deduction feature. This functionality allows inference of new claims from a set of verifiable credentials, making it possible to create stackable credentials and reduce the need for manual checking of verifiable credentials.

This release follows the recent launch of Dock mainnet, which is now flourishing with more than 420,000 blocks produced!

What Is Claim Deduction?

The verifiable credentials issued using Dock are expressed as JSON-LD, which represents a set of semantic knowledge that can be linked together. This format allows computers to evaluate the assumptions and rules in the credentials and reason about them. The result is newly deduced, 'composite' claims that were not explicitly stated in the credentials, but are derived from them. In addition, the reasoning process in our claim deduction feature generates proofs for these composite claims, allowing quick, pragmatic verification.

Claim deduction can be used to create stackable credentials, a sequence of credentials that can be linked to form a larger, overarching credential. This is especially significant for the education and human resources industries, as stacking small certificates earned over one’s career to build a bigger picture of their skill sets is frequently suggested as the future of higher and continuing education. In addition, as you will see in the next section of this post, claim deduction can be integrated with biometrics to fully automate ID verification.

Claim Deduction Demo with Biometrics

We have built a demo to show how claim deduction, facial recognition, and verifiable credentials can be used together to cryptographically verify that a subject is old enough to purchase a restricted item, eliminating the need for manual checks.

It is typically necessary for humans to manually verify credentials when they involve faces. For example, when buying an age-restricted item (e.g., beer) from a store, a customer would present an ID to the cashier, who needs to manually compare the picture on the ID with the customer’s face to ensure that they match. This step introduces friction and inaccuracies in the process, and creates unnecessary physical contact that could be dangerous in this age of a global pandemic.

In our demo, a virtual vending machine takes a verifiable presentation (VP) of a verifiable credential (VC), which contains an image of the subject’s face. When the VP is uploaded, the vending machine will use your device’s camera to determine that you are indeed the subject of the VC. It will also cryptographically verify the VC, and use the claim deduction feature to deduce from the VC whether you are authorized to buy a drink from the machine.

Watch the video below to walk through the demo with Andrew Dirksen, one of our core developers. You can also try the demo for yourself, and read the technical details in our GitHub repository.

Looking Ahead

We are excited by the continued evolution of our infrastructure, and look forward to further expanding our network features and use cases. Adhering to our roadmap, we’re currently wrapping up the security audit of our network, as well as preparing to introduce democracy to the PoA mainnet. In addition, we continue to plan the migration of our existing ERC-20 tokens to the Dock blockchain, and are gearing up to implement anchoring before the end of the year.