A Decentralized Identifier (DID) is a globally unique, persistent identifier that enables verifiable, self-sovereign digital identity without requiring a centralized registration authority. Unlike traditional email addresses or usernames tied to a provider, a DID is controlled entirely by the entity it identifies, using cryptographic proofs to establish ownership and trust.
Glossary
Decentralized Identifier (DID)

What is a Decentralized Identifier (DID)?
A foundational W3C standard for verifiable, user-controlled digital identity that eliminates reliance on centralized registries.
DIDs are the cornerstone of verifiable credential ecosystems, allowing agents to authenticate and communicate securely. A DID resolves to a DID Document stored on a distributed ledger or decentralized network, containing public keys and service endpoints. This architecture enables remote attestation and secure inter-agent communication without a central point of failure.
Core Properties of DIDs
Decentralized Identifiers (DIDs) are a new type of globally unique identifier that enable verifiable, self-sovereign digital identity. Unlike traditional identifiers (email addresses, usernames) issued by centralized authorities, DIDs are fully under the control of the DID subject, providing a foundational layer for trusted agent-to-agent communication.
Decentralization: No Central Registration Authority
DIDs are created and managed without reliance on a centralized registry, identity provider, or certificate authority. Instead, they are anchored on distributed ledger technology (DLT) or other decentralized networks. This eliminates single points of failure and gives the DID subject (the entity identified) exclusive control over their identifier. No third party can revoke, freeze, or take down a DID without the controller's cryptographic keys.
Cryptographic Verifiability
Every DID resolves to a DID document—a JSON-LD file containing the public keys, authentication protocols, and service endpoints associated with the identifier. This cryptographic binding allows any other agent to verify:
- Ownership: The controller possesses the associated private key.
- Integrity: The DID document hasn't been tampered with.
- Authentication: The subject can prove its identity via digital signatures. This is the mechanism that enables trust without a trusted third party.
Persistence and Portability
DIDs are designed to be persistent—once created, they are permanent records on their underlying network. Crucially, they are also portable across service providers. An agent's DID does not change if it migrates from one platform to another. This contrasts sharply with platform-bound identifiers like email addresses or OAuth-based logins, which are tied to a specific provider's domain and can be revoked at any time.
Self-Sovereignty and Control
The DID subject—whether a human, organization, or autonomous agent—holds the cryptographic keys that control the identifier. This principle of self-sovereign identity (SSI) means:
- The subject decides what information to share.
- The subject can rotate keys to maintain security.
- The subject can update service endpoints without permission. For autonomous agents, this enables persistent, self-owned identity across their entire operational lifecycle, independent of any deployment platform.
Interoperability via W3C Standard
DIDs are governed by the W3C Decentralized Identifiers v1.0 specification, ensuring broad interoperability across different networks, ledgers, and implementations. The standard defines a generic syntax (did:method:method-specific-id) and data model. This allows agents on different platforms—Ethereum, ION, or a private ledger—to resolve and verify each other's identities using a universal resolver, preventing vendor lock-in and enabling cross-ecosystem trust.
DID Syntax and Methods
A DID is a URI string with three components separated by colons:
- Scheme: Always
did. - Method: Identifies the specific DID method (e.g.,
ethr,ion,web,key). - Method-Specific Identifier: A unique string within that method's namespace.
Example:
did:ethr:0xE6Fe...a3f4uses the Ethereum network. The method defines how the DID is created, resolved, and managed on a specific underlying system, allowing the ecosystem to support diverse trust models.
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Frequently Asked Questions
Core concepts and common questions about Decentralized Identifiers (DIDs) and their role in establishing verifiable, self-sovereign identity for autonomous agents.
A Decentralized Identifier (DID) is a globally unique, persistent identifier that enables verifiable, self-sovereign digital identity without requiring a centralized registration authority. Unlike traditional identifiers such as email addresses or usernames, a DID is fully under the control of the identity owner—whether a human, organization, or autonomous agent. The identifier is a URI that resolves to a DID Document, a JSON-LD file stored on a distributed ledger or decentralized network. This document contains cryptographic public keys, authentication protocols, and service endpoints that allow other parties to establish secure, trusted interactions. The core mechanism separates the identifier from the identity provider: you prove control over a DID by signing challenges with the private key corresponding to a public key listed in the DID Document, eliminating reliance on third-party certificate authorities or identity providers.
Related Terms
Core concepts that form the decentralized identity stack enabling verifiable, self-sovereign agent credentials and secure inter-agent authentication.
DID Document
A JSON-LD document associated with a DID that contains the cryptographic material, verification methods, and service endpoints necessary for an agent to authenticate and interact securely. This document is stored on a Verifiable Data Registry such as a blockchain or distributed ledger.
- Contains public keys for signature verification
- Lists service endpoints for agent communication
- Supports key rotation without changing the DID
- Enables delegated authority through capability invocation
DID Method
A specification that defines how a specific type of DID and its associated DID document are created, resolved, updated, and deactivated on a particular Verifiable Data Registry. Examples include did:web for domain-based identities and did:ethr for Ethereum-based DIDs.
- did:key: Self-contained, no registry required
- did:web: Resolves via HTTPS from a web domain
- did:indy: Hyperledger Indy for privacy-preserving credentials
- did:ion: Sidetree-based, anchored to Bitcoin
DID Resolution
The process of taking a DID as input and returning the associated DID Document containing the agent's public keys and service endpoints. This is the fundamental operation that enables any party to establish a cryptographically secure communication channel with an agent.
- Performed by a DID Resolver implementation
- Returns DID Resolution Metadata including proof of validity
- Critical for real-time trust establishment between agents
- Must handle deactivated DIDs gracefully
Self-Sovereign Identity (SSI)
A decentralized identity paradigm where an agent or entity has sole ownership and control over its digital identifiers and credentials without reliance on any centralized authority. DIDs are the foundational building block of SSI architectures.
- Portability: Identity moves across systems without permission
- Persistence: Identity survives organizational changes
- Privacy: Minimal disclosure through selective revelation
- Control: The identity owner decides what to share and when
Decentralized PKI (DPKI)
A public key infrastructure where the root of trust is distributed across a blockchain or distributed ledger rather than centralized certificate authorities. DIDs serve as the identifiers in a DPKI, enabling agents to self-certify their public keys.
- Eliminates single points of failure in traditional PKI
- Enables key rotation and revocation without CA involvement
- Supports cross-domain trust without federation agreements
- Uses Merkle trees for efficient key state verification

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
Partnered with leading AI, data, and software stack.
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