MPC for self-sovereign identity
Self-sovereign identity (SSI) is an ever increasingly important concept to enable users control over their own data and let them share it with whom they want. Today, data rests in centralized databases that belong to big enterprises with little transparency into how the data is actually being used and for what purpose.
SSI turns this around and data starts with the users, actually resting at users own device at first. Then it is up to the users to choose with whom and what data they share. Additionally, privacy-preserving features, such as selective disclosure and predicates enhance the user to share data without sharing it all or just prove simple facts about the data.
There are many great tools and infrastructures that can handle SSI, and Partisia Blockchain’s MPC technology adds a new component to the stack that enables new business models, enhances privacy for the data-driven economy, and will take your project ahead of the competition. So read on if you are a builder of the US$27 billion global digital identity market that is expected to expand at a CAGR of 17.2% from 2023 to 2030.
DIDs and verifiable credentials
First things first, digital identity usually revolves around three actors: issuer, holder, and verifier.
The issuer issues verifiable credentials to the holder, and the holder can then present the credentials to a verifier who can verify the content by digital signatures and Decentralized Identifiers (DIDs) that may be on a blockchain. For most digital identity use cases, DIDs and associated DID documents are the only elements that get on the blockchain. We do not take a deep dive on this in this article.
DIDs and verifiable credentials are some of the essential components that make up digital identity, especially digital identity that works with decentralized networks. DIDs are a type of address that is generated to manage digital signatures, and verifiable credentials are credentials created and issued by any issuer based on their DIDs.
To enable real SSI, the users will have to store all data themselves at first, often in digital identity wallets, and only then will the user be in full control. The data itself can be data inputs from users such as personal Identifiable Information (PII) or digital verifiable credentials issued by a third-party, e.g. KYC provider issues KYC claim as digital verifiable credential. Credentials are often issued and exchanged by an agency that establishes secure peer wise connections.
MPC takes digital identity to the next level
Multiparty computation (MPC) is a groundbreaking technology that allows multiple data inputs to remain private while still being computed on and only sharing the outputs. The computing itself is carried out by specially selected MPC validator nodes who each compute on secret shares of the data and privacy is guaranteed by cryptography.
Compared to ZK proofs, such as zk-SNARKs, MPC is a game changer that allows computing on any function. This takes digital identity to the next level because it is now not only possible to share data with privacy features, but also carry out decentralized computation on private data and write business logic into private and public smart contracts to orchestrate the process and rules.
MPC for private data analytics
As we learned before, ZK proofs are good for simple presentations about specific data, e.g. a verifiable credential issued by an employer can be used to prove to the bank that you earn more than US$80,000 a year to qualify for a loan without revealing the exact amount you earn.
Now imagine that we need to compute statistics on multiple inputs from multiple users and compare a single person’s salary to the average, all while preserving privacy. ZK proofs cannot handle general computations on multiple inputs and comparison is limited to two users presenting against each other, so another system would have to support it. This is where Partisia Blockchain’s MPC comes to save the day! MPC on Partisia Blockchain can handle multiple inputs and preserve the privacy while carrying out efficient general computation.
Even though all smart contracts and data can be private, it is often worth considering only to push the most sensitive data and operations into private computation because it is generally more expensive than public computation. This goes for all ZK technology. For instance, if you want to calculate the average salary of employees, you might consider just the salary as private inputs plus pseudonymized identity, and then do statistical calculations in the public space.
MPC for verification
When we look at DID/SSI solutions, the business requirements of the implementation usually go past simple verification of ID. DID/SSI proof is just the first step. The real challenge is what other data do you need after the verification. Perhaps it is to verify that this person has proper credentials for accessing a system. Or another popular use case for DID is to verify a user has enough assets to pay for something without revealing their total asset holding. Another app that is looking to build on our system is trying to create a persona on-chain, which advertisers can target, without revealing personal information about the user themselves.
In all these use cases, a simple proof system becomes too expensive and slow due to the fact that each individual parameter must require a proof. When you have 10 users, maybe this is possible. But what happens when you need to scale to 1000 or 10,000 users? And proofs are not computations. It is unable to compute the various different private data for analysis.
This is where MPC can extend the functionality of DID/SSI to create multi-functional applications. Through MPC you can both prove and compute multiple parameters in a single computation and include all the additional business requirements while keeping the data private.
MPC for Covid-19 passport
During the pandemic, many attempts were made to create a Covid-19 passport so citizens could prove they were either vaccinated or tested negative while preserving privacy. Zk proofs are good for this, but limited to only presenting yes/no results to a verifier without extensive physical verification such as ID cards, which would compromise SSI principles.
In collaboration with HES-SO Valais-Wallis, Partisia Blockchain developed a solution where identification is reduced to matching an individual’s face with an image of the person’s face powered by MPC in order to increase security and privacy. The Partisia Blockchain ensures trustworthy information is broadcasted to the verifier and MPC ensures that the private information about the citizen is used only for matching and kept hidden for the verifier.