Dynamic Transitions of States for Context-Sensitive Access Control Decision

© 2018, Springer Nature Switzerland AG. Due to the proliferation of data and services in everyday life, we face challenges to ascertain all the necessary contexts and associated contextual conditions and enable applications to utilize relevant information about the contexts. The ability to control context-sensitive access to data resources has become ever more important as the form of the data varies and evolves rapidly, particularly with the development of smart Internet of Things (IoTs). This frequently results in dynamically evolving contexts. An effective way of addressing these issues is to model the dynamically changing nature of the contextual conditions and the transitions between these different dynamically evolving contexts. These contexts can be considered as different states and the transitions represented as state transitions. In this paper, we present a new framework for context-sensitive access control, to represent the dynamic changes to the contexts in real time. We introduce a state transition mechanism to model context changes that lead the transitions from initial states to target states. The mechanism is used to decide whether an access control decision is granted or denied according to the associated contextual conditions and controls data access accordingly. We introduce a Petri net model to specify the control flows for the transitions of states according to the contextual changes. A software prototype has been implemented employing our Petri net model for detection of such changes and making access control decisions accordingly. The advantages of our context-sensitive access control framework along with a Petri net model have been evaluated through two sets of experiments, especially by looking for re-evaluation of access control decisions when context changes. The experimental results show that having a state transition mechanism alongside the context-sensitive access control increases the efficiency of decision making capabilities compared to earlier approaches.