AARC and GEANT GN4 projects are studying the Service Provider (SP) communities' (such as research infrastructures, e-infrastructures, communities and research centers) requirements on Level of Assurance (LoA). The survey results will serve the future development of federated authentication and authorization in the set-up where an end user's Home Organisation (e.g. the university or research institute employing the researcher) delivers him/her the authentication credentials and authenticates him/her. The survey results will be published.

1.Introduction to LoA

Narrowly speaking, LoA for user authentication covers two things:

More widely speaking, LoA can also cover e.g.

Some people also count these in

2. Questions on the research infrastructures/communities

Who are your end users (who need to log in to your services):

If you are a research community 

 3.Questions on Identity and Authentication

User's "network identity" distinguishes him/her from other users of the SP.

3.1. Identity concept

How important is it for you that 

3.2.Initial proof of identity

How important is it for you that 

3.3.On-line authentication

3.4.Step-up authentication as a service

Step-up authentication means that the user first authenticates with a password, and subsequently with a second factor (such as by a one-time password delivered to his/her cellphone). Step-up authentication could be delivered to research communities as a service.

Would you like to make use of step-up authentication

4. Questions on user attributes

Besides an identifier, the Home Organisation's Identity Provider is able to deliver also other attributes of the person that logs in.

4.1. Freshness of user accounts and attributes

Many Home Organisations close the user account when an individual departs (e.g. researcher changes his/her employer). Closing the account closes also federated access to your SP. However, some organisations keep the accounts open (e.g. to serve alumni etc).

4.2. Quality/provenance of user data

In larger universities the IdP/IdM gathers users' attributes from several registries (payroll system, CRIS (current research information system), student registry) with varying data quality. Some attributes can even be self-asserted by the user him/herself.

4.3. Population and release of attributes

5.Questions on audits