Automatic Extraction of Petri Nets from RFC Protocol Texts

Request for Comment (RFC) is a universal and standardized specification and describes internet protocol processes, algorithms, and standards. The formal representations of network protocols extracted from RFC can be used to verify correctness and security of the communication process. This paper proposes automatically extracting Petri net models from RFC protocol texts, transforming unstructured protocol text into a structured model. First, the RFC protocol text is preprocessed with chunking, part-of-speech, and element labeling. Second, element recognition is performed by the trained Bert-DGCNN-Bi-LSTM-CRF network, and a structured intermediate representation is generated based on the recognition results and semantic role relationships. Then, state transfer relations are extracted from the intermediate representation and stored in the correlation matrix. The correlation matrix is converted to a PNML file for visualization of Petri nets using PIPE software. Finally, an experimental comparative analysis of element recognition and relation extraction is conducted to prove the effectiveness of the extraction approach. Comparing the similarity between automatic and manual model extraction proves the quality of the extracted models.