Dynamic Behavior Measurement based on Interactive Markov Chain

To deal with challenges and problems in trust measurement, we propose a dynamic behaviors measurement model based on Interactive Markov Chain (IMC). In this model, we use two different ways to obtain system runtime expectations of performance and functions. The one way is Temporal Probability of Executing Routes (TPER), which introduces the relationship between behavior sequences and time. The other is Steady-state Distribution of Executing Routes (SDER), which solves the problem of linear model that can not measure branch and concurrent system. Compared with traditional methods, the IMC-based model provides more powerful ability to measure runtime behaviors in complex and branch system.