a good thing!
Examining the Relevance of Distributed Ledgers to Identity, Part 2
In a previous post, I argued that the appropriateness of a Distributed Ledger (DLT) to a use case depends on whether three criteria are true, specifically:
In this post I'll try to answer the question "Do identity use cases meet the above criteria?" and so explore whether and how DLTs might be relevant to identity and access management (IAM).
Of the above three, the immutability property of DLTs seems hardest to reconcile with identity applications. I argued this point in the first part of this post and won't belabor it here.
I'll focus below on the other two key features of DLT, namely their ability to allow mutually distrusting actors to come to agreement about the existence and ordering of some set of facts shared between them, without that agreement being moderated by a single central party.
A fundamental identity use case is one entity asserting attributes or characteristics of a second. The first entity asserts a value of some attribute for a second entity to a third entity; the third, in the absence of being able to itself confirm the value of those attributes, relies on those assertions and acts accordingly. As a concrete example, in a single sign-on flow, A authenticates the user B and then asserts that fact (plus perhaps some other attributes) to the website or application C where the user wants to access services.
For C to have confidence in the assertion about B that it receives from A, certain questions need to be answered:
Let's consider how DLTs, and specifically their ability to deprecate the need for a third party to mediate the state of some databases, can help answer these questions.
In the above list, the first is a business problem. Only the Government of Canada (GoC) can attest to the fact that I am Canadian. Or, to be precise, only GoC can do so with any credibility. Others can make the claim, but a relying party would have no reason to accept that claim.
And no technical mechanism will ever be able to prevent one business from cheating a business partner for its own advantages by lying about the attributes of the subjects. For instance, if some SaaS were charging its enterprise customers per employee, an enterprise could conceivably minimize its costs by having multiple employees share the same asserted identifier at the SaaS.
So how does C become confident that A is a reputable business that won't completely fabricate the contents of the assertions it creates? Likely by relying on a mix of signals (they have a website and a business credit card or similar indicators of legitimacy) and legal protections should they cheat. Legal protections, of course, imply dependence on a third party, i.e., different levels of government.
The second is a logistical problem. In theory, C could send investigators to examine the processes and technology A has in place to protect its identity management infrastructure from compromise. They could dig into how identities are issued, authenticated and other technical mechanisms. For instance, they might verify that a social provider supports authentication factors beyond password, and so be better able to authenticate its users when doing social login.
Months later the investigators would report back that A runs an efficient shop and does an adequate job of protecting identities. Or not. This sort of direct review would, of course, be expensive and slow. That's why there exists an industry of specialized third-party providers that perform the investigation (for a fee) and attest accordingly.
It is now worth pointing out that DLTs allow parties to come to consensus on the state of the shared ledger; that is, everybody can agree they are all looking at the same set of data. DLTs themselves say nothing about whether that data is actually true. E.g., everybody can come to agreement that the database includes the statement "The sky is green."
Given that, I don't see DLTs offering any unique value in helping the relying party C answer these first two questions. Both demand that C make a value judgement, e.g., that A is "good" at something, and DLTs will never help with that, other than merely providing a place where other parties recommendations about A could be stored. But that, of course, reintroduces a third party into the mix that DLTs promised us to do away with.
The third requirement is a technical problem: How can we deliver an assertion over the (likely public) network so that we prevent a malicious actor interfering with that transmission for nefarious purpose?
It is on this third requirement that different identity standards and models differ--and where I believe that DLTs can offer value (albeit with tradeoffs) relative to other models.
Every identity system can be characterized and differentiated by how it answers the following questions (which determine the how, what, and when an assertion is shared):
As an example, a deployment of SAML in support of employees accessing SaaS applications might answer the above questions as:
A deployment of OpenID Connect for social login would have similar answers for #2, #3, and #4, but would likely replace role attributes of #1 with profile info or social streams.
In a typical deployment of the SAML and Connect models, the asserting party (the identity provider) is involved in the real-time delivery of the identity assertion to the application. This involvement has a number of consequences, including:
For some, these consequences give too much power or knowledge to the identity provider and too little empowerment to the user. Using the analogy I introduced in the first part, they see the SAML and Connect models as "placing too many privacy eggs in the IdP basket." Such critics contrast it with the real-world example of somebody being able to purchase alcohol by presenting a driver's license proving their legal age, where DMV, the agency that issued the license, is unaware that the user is buying alcohol and has no ability to prevent the user from doing so.
The Self Sovereign Identity (SSI) community is proposing an identity model that de-emphasizes the real-time involvement of the identity provider and so aims to mitigate the above concerns. SSI still recognizes the value of certain parties being authoritative over certain identity attributes (e.g. the DMV for driving ability) but argues the benefits of disintermediating those asserting parties from being actively involved in the sharing and presentation of the assertions.
In the absence of an identity provider creating identity assertions on a just-in-time fashion in response to a request from a relying party, we need an alternative issuance-delivery-validation model. The SSI community advocates introducing a DLT into the mix, specifically to store references to user identity assertions stored off-ledger.
Critically, in SSI models, identity assertions are issued ahead of time rather than at the real-time behest of a relying party. This, of course, means that identity assertions are not created for the particular relying parties to which they will be presented. Like a real-world driver's license, the SSI assertions are not targeted for a specific audience.
In the SSI model, a DLT is merely a place where the identity provider can add pointers (not the assertions themselves for privacy reasons) to the assertions it makes. A DLT provides a shared database where IdPs can logically place assertions about user identity attributes and relying parties can subsequently look them up. A user lays claim to those assertions by demonstrating they have possession of an associated crypto key when interacting with a relying party.
The DLT serves to distance the IdP from the RP, and so mitigate the concerns listed above where the IdP was perceived to have excessive power and control. Instead of using a DLT, all IdPs could place their assertions into some centralized database. But this just shifts the problem and gives to that single central database inappropriate visibility and control into a user's identity operations.
So the SSI model and its usage of a DLT may offer privacy advantages relative to the web redirect model normalized by SAML and OpenID Connect. But there are, of course, tradeoffs. In the next post in this series, I'll explore what those tradeoffs might be.