Learning Machine wins DHS Grant to align Blockcerts with the W3C specifications for Verifiable Credentials and Decentralized Identifiers.
When Blockcerts was incubated at MIT, it was the first open-source project in the world that demonstrated how to create, issue, and verify a digital record using a blockchain to ensure the integrity of that record. At the time, Bitcoin was widely considered the most viable blockchain, and the W3C Verifiable Credentials specification was still nascent. Nevertheless, the project moved forward with a commitment to the principles of openness, synchronization with other data standards, recipient control, vendor independence, and viability for any blockchain.
Since the launch of Blockcerts, major strides have been made in the Self-Sovereign Identity (SSI) space thanks to the diligent work of groups like the W3C, Rebooting Web of Trust, the Internet Identity Workshop, and the Decentralized Identity Foundation, all of which have built upon 20+ years of hard work from many different companies, organizations, and individuals.
Today, with the emergence of the Verifiable Credentials specification, Decentralized Identifiers (DIDs), a Universal Resolver, and other important components of self-attesting digital credentials, the world has a set of tools and specifications which lay the groundwork for a growing consensus about methods and formats that can reliably assert a digital claim. Most importantly, these standards are not owned by any one vendor or institution, making them an infrastructure that enables open innovation. The W3C credential standards are analogous to TCP/IP or GPS: open protocols that enabled the internet and geolocation revolutions.
Governments are playing an increasingly critical role in the verifiable credentials ecosystem by funding fundamental research. An important example of governments taking the lead in this way is the Silicon Valley Innovation Program, part of the U.S. Science & Technology directorate within the Department of Homeland Security. SVIP offers a variety of grants to help develop new technologies and accelerate their time to market.
Today, Learning Machine is proud to announce that we have won Phase-1 funding for our response to the open call “Preventing Forgery & Counterfeiting of Certificates and Licenses through the use of Blockchain and Distributed Ledger Technology.” The purpose of the call was to develop vendor-neutral technology solutions that prevent the forgery and counterfeiting of official records for immigration, travel, visas, and other use cases pertaining to national and citizen security. Our grant application addressed DHS requirements by proposing an upgrade to the Blockcerts open standard, making it capable of issuing W3C Verifiable Credentials. The open-source reference implementation, targeted for 2020, will include:
- Updating the Blockcerts schema to a Verifiable Credentials-based format
- Updating the Blockcerts signature/verification scheme to conform to the latest JSON-LD signature suite format
- Updating Blockcerts credential issuance and verification
- Incorporating a cost-efficient DID method for issuers
All of these upgrades to the Blockcerts open standard will also be included in Learning Machine’s SaaS product for issuing digital credentials. By becoming fully aligned with the W3C, Blockcerts (and, by extension, Learning Machine customers) will benefit from many security and feature upgrades. View the DHS Press Release about Learning Machine.
The Blockcerts roadmap has always aimed to enable the issuance and verification of an ever-wider range of credentials, along with related privacy-enhancing measures. These are largely achieved by alignment with Verifiable Credentials and the Decentralized Identifier specifications, which promise the following benefits:
Verifiable Credentials allows for flexible data schemas at its core, allowing for a wider range of credentials all backed by a greater range of security and privacy-protecting features.
The use of DIDs removes the need to rely on issuer-hosted profiles and revocation lists, which creates unwanted dependency on the issuing institution. This enhances auditability of credentials and has many security benefits for key management. Most importantly, however, it ensures that credentials issued by an institution will continue to verify even if that institution no longer maintains its own hosting infrastructure–critical for the long-term ownership and verification of records across time and geographic boundaries.
Improved Privacy and Security
- New strategies help to avoid correlation of data between credentials. Currently, data aggregation is dangerous because even anonymized data can be correlated to individuals. Working together, the Verifiable Credentials and DIDs specifications make it much more difficult for any actor to correlate data without the data subject’s knowledge or consent.
- Enabling the selective disclosure of credential data allows individuals to choose which data points they share with whom, rather than sharing an entire record that includes data that might not be relevant to the transaction at hand. This conforms to the principle of “data minimization,” a key component of self-sovereign identity.
A Global Standard
The W3C specification offers a world-wide data standard which catalyzes global alignment and thereby facilitates interoperability for all digital claims made on the web or shared peer-to-peer.
At Learning Machine, we’re proud to help bring these standards into an open-source reference implementation at Blockcerts.org, as well as within the world’s leading commercial system for issuing and managing blockchain credentials. Our ability to translate these complex technology standards into convenient products will make it easy for governments, education providers, companies, and others to issue a full range of Verifiable Credentials.