Digital Identity Management for AI Agent Communication Protocols
draft-yl-agent-id-requirements-00

Network Working Group                                             K. Yao
Internet-Draft                                                    P. Liu
Intended status: Informational                              China Mobile
Expires: 2 January 2026                                      1 July 2025

    Digital Identity Management for AI Agent Communication Protocols
                   draft-yl-agent-id-requirements-00

Abstract

   AI agents are rapidly and massively transitioning from cutting-edge
   technology into real life.  The AI agent communication protocol will
   establishing a critical means to connect agents with different users,
   tools, and other agents.  Among all the features of AI agent
   communication protocol, digital identity is one of the most important
   components.  Developing a cross-industry, universal, flexible,
   interoperable, and secure AI agent digital identity protocol is the
   foundation for achieving communication between agents and other
   entities in future network.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Digital Identity Management Related Use Cases in the Context of
           AI Agent Communications . . . . . . . . . . . . . . . . .   3
     2.1.  General . . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Potential Digital Identity Management Requirements for AI Agent
           Communication . . . . . . . . . . . . . . . . . . . . . .   5
     3.1.  General . . . . . . . . . . . . . . . . . . . . . . . . .   5
     3.2.  Identifier  . . . . . . . . . . . . . . . . . . . . . . .   5
       3.2.1.  Global Unique Identifier  . . . . . . . . . . . . . .   5
       3.2.2.  User Binding  . . . . . . . . . . . . . . . . . . . .   5
     3.3.  Attribute . . . . . . . . . . . . . . . . . . . . . . . .   5
       3.3.1.  Skill . . . . . . . . . . . . . . . . . . . . . . . .   5
       3.3.2.  Capability  . . . . . . . . . . . . . . . . . . . . .   5
       3.3.3.  Service . . . . . . . . . . . . . . . . . . . . . . .   6
       3.3.4.  Key Credential  . . . . . . . . . . . . . . . . . . .   6
     3.4.  Security  . . . . . . . . . . . . . . . . . . . . . . . .   6
       3.4.1.  Authentication  . . . . . . . . . . . . . . . . . . .   6
       3.4.2.  Authorization . . . . . . . . . . . . . . . . . . . .   6
     3.5.  Discovery . . . . . . . . . . . . . . . . . . . . . . . .   7
       3.5.1.  Intra-domain  . . . . . . . . . . . . . . . . . . . .   7
       3.5.2.  Inter-domain  . . . . . . . . . . . . . . . . . . . .   7
   4.  Security Considerations . . . . . . . . . . . . . . . . . . .   7
   5.  Conclusions . . . . . . . . . . . . . . . . . . . . . . . . .   7
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   7.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .   8
   8.  Informative References  . . . . . . . . . . . . . . . . . . .   8
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   In recent years, large model-based generative AI is rapidly
   advancing, paving the way for the arrival of AGI.  Technically, the
   large model has evolved from the single-modal LLMs like ChatGPT to
   multi-modal Vision-Language Models (VLMs) such as DALL-E, SORA, and
   GPT-4o.  It now evolves to the Vision-Language-Action (VLA) models
   for robot control, like Google's RT-2 and RT-H.

   A large number of new intelligent terminals emerge, and embodied AI
   is poised to become the most valuable application of AI.  A plethora
   of traditional terminals are being upgraded to AI ones through
   embedded large models and AI agents, for example, AI phones, AI

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   wearables, and AI PCs.  In addition, embodied AI comes in.  It refers
   to intelligent agents that can understand, reason, and interact with
   the physical world, such as intelligent robots, self-driving cars,
   and robot dogs.  Humanoid robots are one of the core scenarios of
   embodied AI.  According to the prediction of GGII, the global
   humanoid robot market is projected to grow from USD 1.017 billion in
   2024 to USD 15 billion in 2030, increasing at a compound annual
   growth rate (CAGR) of 56%. The global sales volume of humanoid robots
   will increase from 11,900 to 605,700.

   Everyone may have a virtual intelligent assistant.  AI agents
   understand user needs, schedule tasks, and invoke and combine massive
   applications autonomously.  AI agents will revolutionize application-
   centric development mode and Graphic User Interface (GUI)-based
   human-machine interaction.  This innovation leads to entries for
   super applications and super traffic.  Many relavant use cases have
   been mentioned in [I-D.rosenberg-ai-protocols].

   These AI agents are poised to be the "new citizens" of future network
   connections, heralding an economic boom and ushering human social
   life into a new era of collaboration between humans and AI agents, as
   well as among AI agents themselves.

2.  Digital Identity Management Related Use Cases in the Context of AI
    Agent Communications

2.1.  General

   According to ITU-T [Digital-identity], the digital identity is
   defined as follows:

   Digital Identity: The International Telecommunication Union (ITU)
   defines the concept of identity as a ‘representation of an entity in
   the form of one or more attributes that allow the entity or entities
   to be sufficiently distinguished within context’. Building on this
   definition, we might state that a digital identity is the digital
   representation of an entity detailed enough to make the individual
   distinguishable within a digital context.

   According to 3GPP [TR22.870], an AI agent is defined as follows:

   Al Agent: an automated intelligent entity capable of e.g. interacting
   with its environment, acquiring contextual information, reasoning,
   self-learning, decision-making, executing tasks (autonomously or in
   collaboration with other Al Agents) to achieve a specific goal.

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   Thus the digital identity of an AI agent could be defined as “the
   digital representation of an AI agent detailed enough to make
   individual distinguishable within an AI agent communication context.”
   The digital identity contains mainly 3 parts: identifier, attribute
   and key credential.

2.2.  Use Cases

   According to 3GPP TR 22.870, there are some use cases discussing AI
   agent that communicate from/to terminal side with the support of
   digital identity.

   AI agents communication: - As communication serves as a common
   mechanism for sharing information, there will be more and more users
   and their AI agents that need to be supported in a near future.  A
   group could be established for users and their AI agents to
   communicate with each other.  To complete a complex task involving
   multiple users and triggered by a user, AI agent or application,
   communication domain for multiple groups could be established, the
   users and AI agents working for the same task can be explicitly
   identified by the task request or implicit identified based on
   location area or relative distance.  Communication domain could be
   dynamically created for users and AI agents from multiple groups to
   communicate with each other for a specific task during a specific
   time.  Only the AI agents in the same domain can communicate with
   each other.  If authenticated / authorized, users and AI agents could
   join this group via various access technologies, including the
   cellular network, Wi-Fi and Ethernet, etc.

   Intelligent Communication Assistants: - Overall, intelligent
   communication assistant provided by the operators natively is a
   customized service.  It can interact with end users through voice,
   text, gesture or other modalities to provide enhanced experience.
   The assistant can be customized for each particular user by accessing
   user data stored in the network.  With user’s consent, it can provide
   various communication services and support individual users based on
   user’s intention and requirement.  The provided services include
   intent-based search, personalized recommendations, voice-controlled
   smart home devices, and interaction with various services (including
   3rd party AI assistant or capabilities) or devices.  The
   customization can be achieved by providing different levels of the
   intelligent communication assistant service, based on the
   authorization from the user for user data.

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3.  Potential Digital Identity Management Requirements for AI Agent
    Communication

3.1.  General

   Digital Identity in the context of AI agent communication involves
   several common requirements to ensure effective, efficient, and
   secure interactions.  Here is a list of potential key requirements
   derived from the illustrative use cases provided in the previous
   sections.  They are not yet formally approved by 3GPP and only
   provided for information/discussion.

3.2.  Identifier

3.2.1.  Global Unique Identifier

   AI agents SHOULD have a global unique identifier in an universal
   interoperable format to ensure the identifier can be used to
   dynamically identify and locate the AI agent.

3.2.2.  User Binding

   AI agents are designed to provide services for the human user,
   sometimes on behalf of the user.  The digital identity of an AI agent
   MUST support the description of its associated user, so that the AI
   agent communication protocol can further support user authorization
   when needed.

3.3.  Attribute

3.3.1.  Skill

   AI Agents can support multiple skills, and these skills may not be
   provided by a single manufacturer or provider.  Considering that
   skill is the nature of AI agent communication and one of the most
   important properties of an AI agent.  The definition of skills with
   different origins for an AI agent SHOULD be supported.

3.3.2.  Capability

   AI agent are able to communicate with other agents through multi-
   modal capabilities, e.g. text, image, voice, video, real-time
   communication.  These capabilities are pre-requisites for the
   communication channel establishment.  The definition of these multi-
   modal capabilities SHOULD be supported.

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3.3.3.  Service

   AI Agent SHOULD be able to obtain long-term or short-term service
   verifiable credentials from different service providers, these
   credentials can be used for access control purposes.  The AI agent
   identity SHOULD support the definition of dynamic service attributes.

3.3.4.  Key Credential

   AI Agent SHOULD be able to support transmit, share, store its digital
   identity in a secure way.  Usually the public key credential is used
   to ensure the integrity of digital identity.  Also the key credential
   can be used by the target entity of the AI agent to verify its
   identity information.  The AI agent identity SHOULD support the usage
   of key credential.

3.4.  Security

3.4.1.  Authentication

   In addition to traditional user authentication, the authentication of
   the agent should also be considered in AI agent identity management.
   More AI agent authentication related considerations have been
   mentioned in [I-D.yao-agent-auth-considerations].  The digital
   identity SHOULD contain at least one corresponding credential for the
   unique identifier for the identification.

3.4.2.  Authorization

   According to different scenarios, there will be three different
   authorization requirements, the digital identity of AI agent SHOULD
   support these authorization requirements.

   *  Agent Authorization:

   The agent authorization is the common authorization that agent A
   provides authorized information from its own digital identity needed
   by agent B, and then agent B verifies and authorize the request.
   This is REQUIRED when an agent is on-behalf-of(OBO) itself or other
   agents.

   *  Delegation Authorization:

   The agent authorization is the common authorization that Agent A
   provides authorized information from its user’s and own digital
   identity needed by Agent B, and then Agent B verifies and authorize
   the request.  This is REQUIRED when an agent is OBO its user, itself,
   or other agents.

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   *  User Authorization:

   The agent authorization is the common authorization that agent A
   provides authorized information from its user’s and own digital
   identity needed by agent B, and then agent B still thinks that it’s
   not sufficient, then agent B require agent A to help get a direct
   authorized information from the user to avoid risk.  This is REQUIRED
   when an agent is OBO its user.

3.5.  Discovery

3.5.1.  Intra-domain

   *  Registration: In order for a successful discovery, the AI agent
      SHOULD be able to register its digital identity in an intra-domain
      repository.  So that the AI agent can be discovered by the intra-
      domain entities (e.g. user/other agents).

3.5.2.  Inter-domain

   *  Discovery mechanism: AI agent should be able to find needed
      resource (user/tool/agent) dynamically through discovery mechanism
      depending on identifier or attribute, from intra-/inter-domain
      repositories to meet its task requirements.  The digital identity
      of AI agent should be the bearer of discovery information.

   *  Repository Update and Synchronization: In order for a successful
      discovery, different AI agent repositories SHOULD be able to
      update the digital identity information of AI agents that can be
      discovered.

4.  Security Considerations

   As discussed in previous sections, security plays a key roles in the
   definition of digital identity of AI agent.  A comprehensive
   consideration of the potential impact of the various specific
   technologies that may be involved on the overall AI agent
   communication protocol is required.

5.  Conclusions

   AI agent communication requires the participation of partners from
   the industry, academia, and research sectors, including terminal
   vendors, network service providers, cloud service suppliers, AI base
   model providers, and application developers.  Through technical
   workshops, project collaboration, and innovation pilots, all parties
   should join efforts to make AI agent communication an essential part
   of AI agent economic growth in the future.  Furthermore, the industry

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   should advance the standardization progressively to formulate
   globally unified standards for the AI agent communication and prosper
   the industry ecosystem.

   In summary, while AI agents have impressive autonomy and
   intelligence, they are ultimately tools that serve the needs of
   individuals or organizations.  Each AI agent possesses a unique
   digital identity bound to the user identity they serve on the
   network.  After AI agents are authenticated and authorized, their
   autonomous communication activities can be supervised, controlled,
   and traced on the network by the user.  Also, diverse AI agents
   possess varying levels of sensing, decision-making, and operational
   capabilities.  Besides autonomy, these properties can be shared with
   other AI agents through discovery and orchestration, facilitating
   task collaboration and achieving the effect of collective
   intelligence.

   Standard solutions will be required to support the management of
   digital identity for AI agent communications.  To ensure the global
   interoperability between heterogeneous AI agents, a standardized AI
   agent communication protocol including the digital identity
   management needs to be introduced for the session establishment and
   multi-modal data transmission.  It is expected that IETF could be the
   place to develop such standard.

6.  IANA Considerations

   TBD.

7.  Acknowledgements

8.  Informative References

   [Digital-identity]
              ITU-T, "Digital Identity Roadmap Guide, D-STR-
              DIGITAL.01-2018-PDF-E.", n.d..

   [I-D.rosenberg-ai-protocols]
              Rosenberg, J. and C. F. Jennings, "Framework, Use Cases
              and Requirements for AI Agent Protocols", Work in
              Progress, Internet-Draft, draft-rosenberg-ai-protocols-00,
              5 May 2025, <https://datatracker.ietf.org/doc/html/draft-
              rosenberg-ai-protocols-00>.

   [I-D.yao-agent-auth-considerations]
              Yao, K., "Further considerations on AI Agent
              Authentication and Authorization Based on OAuth 2.0
              Extension", Work in Progress, Internet-Draft, draft-yao-

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              agent-auth-considerations-00, 30 June 2025,
              <https://datatracker.ietf.org/doc/html/draft-yao-agent-
              auth-considerations-00>.

   [TR22.870] 3GPP, "Study on 6G Use Cases and Service Requirements",
              n.d..

Authors' Addresses

   Kehan Yao
   China Mobile
   Email: yaokehan@chinamobile.com

   Peng Liu
   China Mobile
   Email: liupengyjy@chinamobile.com

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