2010
DOI: 10.1016/j.future.2009.12.004
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A conceptual model for attribute aggregation

Abstract: This paper describes a conceptual model for attribute aggregation that allows a service provider (SP) to authorise a user's access request based on attributes asserted by multiple identity providers (IdPs), when the user is known by different identities at each of the IdPs. The user only needs to authenticate to one of the IdPs and the SP is given an overall level of assurance (LoA) about the authenticity of the user and his/her attributes. The model employs a new component called a Linking Service (LS), which… Show more

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Cited by 16 publications
(16 citation statements)
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“…Chadwick et al [34] developed another model by introducing a new SP called a linking service (LS). This conceptual model satisfies most of the identity management requirements and allows the collection of attributes from various sources.…”
Section: Related Workmentioning
confidence: 99%
“…Chadwick et al [34] developed another model by introducing a new SP called a linking service (LS). This conceptual model satisfies most of the identity management requirements and allows the collection of attributes from various sources.…”
Section: Related Workmentioning
confidence: 99%
“…Therefore, user impersonization by identity providers is inherent to the FIM model. Moreover, attribute aggregation [7] is often not supported. Further, many identity providers still use password based authentication since often no infrastructure for strong authentication is available.…”
Section: Related Workmentioning
confidence: 99%
“…That is, neither the identity of the subject giving feedback nor the identity of the object on which feedback is given may change over multiple sessions or vary for different service providers. The TAS 3 architecture provides a federated identity management (FIDM) which lets users use different, non-linkable identifiers at different services and provides a linking service [7] with which users can combine attributes provided by different identity providers. This allows users to increase the impact of their feedback by linking relevant attributes without revealing their identity.…”
Section: Privacy Enhancement For Rtmmentioning
confidence: 99%