An event driven hybrid identity management approach to privacy enhanced e-health.
Credential-based authorization offers interesting advantages for ubiquitous scenarios involving limited devices such as sensors and personal mobile equipment: the verification can be done locally; it offers a more reduced computational cost than its competitors for issuing, storing, and verification; and it naturally supports rights delegation. The main drawback is the revocation of rights. Revocation requires handling potentially large revocation lists, or using protocols to check the revocation status, bringing extra communication costs not acceptable for sensors and other limited devices. Moreover, the effective revocation consent--considered as a privacy rule in sensitive scenarios--has not been fully addressed. This paper proposes an event-based mechanism empowering a new concept, the sleepyhead credentials, which allows to substitute time constraints and explicit revocation by activating and deactivating authorization rights according to events. Our approach is to integrate this concept in IdM systems in a hybrid model supporting delegation, which can be an interesting alternative for scenarios where revocation of consent and user privacy are critical. The delegation includes a SAML compliant protocol, which we have validated through a proof-of-concept implementation. This article also explains the mathematical model describing the event-based model and offers estimations of the overhead introduced by the system. The paper focus on health care scenarios, where we show the flexibility of the proposed event-based user consent revocation mechanism.
Department of Telematic Engineering, Carlos III University of Madrid, Avda. Universidad 30, 28911, Leganes, Madrid, Spain. rmsguerr@it.uc3m.es
Rosa
R
Sánchez-Guerrero
Florina
F
Almenárez
Daniel
D
Díaz-Sánchez
Andrés
A
Marín
Patricia
P
Arias
Fabio
F
Sanvido
D006801:Humans; D016347:Medical Records Systems, Computerized; D009042:Motivation; D010355:Patient Identification Systems; D018907:Privacy