Paper detail

FORT: Right-proving and Attribute-blinding Self-sovereign Authentication

Nowadays, there is a plethora of services that are provided and paid for online, like video streaming subscriptions, car or parking sharing, purchasing tickets for events, etc. Online services usually issue tokens directly related to the identities of their users after signing up into their platform, and the users need to authenticate using the same credentials each time they are willing to use the service. Likewise, when using in-person services like going to a concert, after paying for this service the user usually gets a ticket which proves that he/she has the right to use that service. In both scenarios, the main concerns are the centralization of the systems, and that they do not ensure customers' privacy. The involved Service Providers are Trusted Third Parties, authorities that offer services and handle private data about users. In this paper, we design and implement FORT, a decentralized system that allows customers to prove their right to use specific services (either online or in-person) without revealing sensitive information. To achieve decentralization we propose a solution where all the data is handled by a Blockchain. We describe and uniquely identify users' rights using Non-Fungible Tokens (NFTs), and possession of these rights is demonstrated by using Zero-Knowledge Proofs, cryptographic primitives that allow us to guarantee customers' privacy. Furthermore, we provide benchmarks of FORT which show that our protocol is efficient enough to be used in devices with low computing resources, like smartphones or smartwatches, which are the kind of devices commonly used in our use case scenario.

preprint2022arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.