Capturing Dynamicity and Uncertainty in Security and Trust via Situational Patterns.

Modern smart systems are highly dynamic and allow for dynamic and ad-hoc collaboration not only among devices, but also among humans and organizations. Such a collaboration can introduce uncertainty to a system, as behavior of humans cannot be directly controlled and the system has to deal with unforeseen changes. Security and trust play a crucial role in these systems, especially in domains like Industry 4.0 and similar. In this paper we aim at providing situational patterns for tackling uncertainty in trust – in particular in access control. To do so, we provide a classification of uncertainty of access control in Industry 4.0 systems and illustrate this on a series of representative examples. Based on this classification and examples, we derive situational patterns per type of uncertainty. These situational patterns will serve as adaptation strategies in cases when, due to uncertainty, an unanticipated situation is encountered in the system. We base the approach on our previous work of autonomic component ensembles and security ensembles.