Drafting Note: This is a straw man outline to kick start the drafting process. None of this is written in stone.


  • To be completed after drafting.


This document sets out the privacy and identity-related considerations for mobile driving license ecosystems from the perspectives of issuing authority, the holders of mobile driving licenses, and the verifiers of mobile driving licenses. …

The intended audience for this document is the producers and users of mobile driving license readers who will want to demonstrate conformance with privacy and identify protection standards in their jurisdictions. …

This report proposes the creation of a trust framework for mDL ecosystems, including trust levels and attribute assurances to enable a robust and privacy-protective system for all stakeholders. ...


From the charter

mDL Ecosystem Architectures

Explanatory text to be added

ISO/IEC 18013-5

Placeholder Image for mDL architecture

Verified Credentials

Self-Sovereign Identity

MyData Operators ecosystem


At a high level, mobile Driving Licenses are a credential that can be used by individuals in person or remotely to provide identity proofs, validate limited identity attributes, or as an authentication mechanism. mDL ecosystems will intersect with other ecosystems or architectures for identity systems as shown below. Ensuring that Identity Proofing and Privacy Protections can be applied at the point of identity verification will require common touchpoints in ecosystems for interoperability and mutual assurance. This section of the report describes ecosystems that will need to interoperation with mDL ecosystems

Sample Use Cases

Law Enforcement



Template Use Case

Create a template below to be used above.

Privacy Considerations

This section is based on Annex E of ISO/IEC 18013-5, as expanded by the Kantara Discussion Group.

ISO/IEC 18013-4, s E.2.1 states

Individual privacy and security of personally identifiable information (PII) in the mobile, electronic age must be ensured and is a shared responsibility of all involved parties. No technical standard for data interchange can dictate how all privacy measures are achieved. Privacy is achieved by the end-to-end solution, and with the participation of all participants in an ecosystem. Each actor in the mDL ecosystem should fulfill their role in a responsible manner that best protects PII.

Identity Considerations

See other Kantara work on Identity proofing

Recommended Conformance Tests



Acronyms and Terms


Application Protocol Data Unit
BERBasic Encoding Rules
BLEBluetooth Low Energy
BT SIGBluetooth Interest Group

Certificate Authority

CBORConcise Binary Object Representation
CDDLConcise data definition language
COSECBOR Object Signing and Encryption
CSPRNGCryptographically Secure
CRLCertificate Revocation List
DERDistinguished Encoding Rules
DOData Object
DSDocument Signer
ECDHElliptic Curve Diffie-Hellman
ECDSAElliptic Curve Digital Signature Algorithm
EdDSAEdwards-curve Digital Signature Algorithm
GATTGeneric Attribute Profile
GUIDGlobally Unique Identifiers
HKDFHMAC-based Extract-and-Expand Key Derivation Function
IAIssuing Authority
IACAIssuing Authority Certificate Authority
IAPCIssuing Authority Point of Contact
IDLISO-compliant driving licence
IKMInput Keying Material
JWSJSON Web Signature
JWAJSON Web Algorithms
KDFKey Derivation Function
MACMessage Authentication Code
MITMMan-in-the-middle attack
MLMaster List
MSOMobile Security Object
MTUMaximum Transmission Unit
NDEFNFC Data Exchange Format
NFCNear Field Communication
OCSPOnline Certificate Status Protocol
OIDObject Identifier
OIDCOpenID Connect
PIXProprietary Application Identifier Extension
PKIPublic Key Infrastructure
RIDRegistered Application Provider Identifier
TLSTransport Layer Security
TLVTag Length Value
UHFUltra-High Frequency
URIUniform Resource Identifier
URLUniform Resource Locator
UTCCoordinated Universal Time
UUIDUniversally unique identifier