  Personalization and adaptation to the user profile capability are the hottest
issues to ensure ambient assisted living and context awareness in nowadays
environments. With the growing healthcare and wellbeing context aware
applications, modeling security policies becomes an important issue in the
design of future access control models. This requires rich semantics using
ontology modeling for the management of services provided to dependant people.
However, current access control models remain unsuitable due to lack of
personalization, adaptability and smartness to the handicap situation. In this
paper, we propose a novel adaptable access control model and its related
architecture in which the security policy is based on the handicap situation
analyzed from the monitoring of userss behavior in order to grant a service
using any assistive device within intelligent environment. the design of our
model is an ontology-learning and evolving security policy for predicting the
future actions of dependent people. This is reached by reasoning about
historical data, contextual data and user behavior according to the access
rules that are used in the inference engine to provide the right service
according to the users needs.
