Extracting Rules from Specifications and Their Modeling using Colored Fuzzy Petri-Nets

In this paper, the rules governing the behavior of the system are extracted from the system specifications and then they are modeled by Petri-nets. The set of these rules forms knowledge base of the system, which provides the ability of making inferences. Each rule consists of several premises and a conclusion. When there are many rules and the premises in different rules overlap, it is possible to prevent the repetition of premises using a hierarchical structure by the inference engine and thus reduce the number of checks required to reach the conclusion. When these rules have many and fuzzy variables, they take a complex form, and it becomes difficult to understand and deduce their behavior. To better understand this complexity, it is appropriate to visualize it using fuzzy petri-nets. So far, many different methods based on fuzzy Petri-nets have been presented to model fuzzy rules. But these methods either do not support the large number of rules and variables or do not consider matters like the role of conditional propositions in the occurrence of the conclusion propositions, the probability of the conclusion propositions, the threshold value for the conditional propositions and the conclusions, the certainty factor for the rule or for the conditional propositions. In this paper, by extending our previous work, we present a model based on fuzzy Petri-nets that covers the two mentioned cases. Finally, we present the proposed model for a secure water refinement system and the attacks against it.