Issuing and Verifying JSON-LD Credentials with ACA-Py

Added:

LDPVC Basics
Use Cases
VC Data Model
Context Property
Credential Fields
ACA-Py Issuing
ACA-Py Presenting
Demo Walkthrough
Limitations

LDPVC Basics

4:03
Playing Section
  • 1

    Defines JSON-LD credentials as W3C VC format using linked data proofs.

  • 2

    Compares LDPVC with other types like AnonCreds and JWT VCs.

  • 3

    Explains that the unique format and crypto combination defines a credential type.

Fundamental concepts of Self-Sovereign Identity (SSI), including Decentralized Identifiers (DIDs) and the W3C Verifiable Credentials data model.
Understanding of JSON-LD (JSON for Linking Data) structures, schemas, and semantic web context mapping.
Familiarity with Hyperledger Aries architecture and the role of cloud agents (like ACA-Py) in agent-to-agent communication.
Basic proficiency in Python programming and working with RESTful APIs for agent administration.
Implementing advanced cryptographic signature suites, such as BBS+ Signatures, to enable selective disclosure and zero-knowledge proofs.
Configuring multi-ledger DID resolution using ACA-Py with different DID methods (e.g., did:indy, did:web, or did:ion).
Designing and building mobile or web-based identity wallets that interact with ACA-Py via standard DIDComm protocols.
Establishing organizational governance frameworks and trust registries for scaling credential ecosystems in production environments.
1.5K views23likes1:00:26@IndicioIDOriginal Release: 2022-11-29

JSON-LD Verifiable Credentials (LDPVC) are W3C-compliant credentials that use Linked Data Proofs for cryptographic verification, offering advantages over AnonCreds including simpler cryptography (ed25519 signatures) suitable for IoT environments, the ability to present credentials about subjects other than the holder, and support for complex nested data structures. ACA-Py (Aries Cloud Agent - Python) supports issuing and verifying these credentials through version 2 protocols, which differ from AnonCreds V1 by allowing holders to initiate credential requests directly without proposal-offer cycles and by generalizing credential formats through attachment-based specifications. The VC data model defines two distinct objects: verifiable credentials (claims made by issuers) and verifiable presentations (data derived from credentials shared with verifiers), enabling selective disclosure and holder-subject binding proofs.