Scenario-based trustworthiness verification for systems of internet of things. (2018) - Zhang, Junhua; Zhu, Yi
Assessment of the running quality for internet of things (IoT) is an important scientific question. In this paper, we adopt model checking to solve this question. We extend living sequence chart (LSC) with time to model the demand for a system of IoT, and further add probability element to model the system itself. We present a framework to transform LSC with extensions into corresponding automata based on meta-model. So the model checking question between LSCs is changed into for automata. Through modifying and composing the obtained automata, we can obtain a standard probabilistic timed automaton. By inputting it into probabilistic model checker PRISM, we can calculate a probability, which reflecting the satisfying level of the original system to the demands. Since the system model which we use is more intuitive than classical formal model, it can be used more easily.