# A Novel Network Protocol Syntax Extracting Method for Grammar-Based Fuzzing
## 6 Conclusions and Future Work  
In this work, we propose a novel method for extracting network protocol syntax information. The method can extract all packet types of the target protocol and all field information for each packet type by automatically analyzing the Wireshark protocol dissector file. We designed a protocol syntax information extraction system based on this method and applied it to the Modbus TCP, Modbus RTU, DCCP, DNP3.0, and S7 COMM protocols. Experimental results show that our method can effectively extract most packet types of the protocol, the constituent fields of each packet type, and the dependencies between the fields. Using the extracted syntax information for network protocol fuzzing can increase the effectiveness of the test-case generating process, and improve the efficiency and path coverage depth of fuzzing. By comparing with manual methods, traffic-based methods, and artificial intelligence methods, our method has a better performance in terms of automation, process time per protocol, applicability, and cost; at the same time, the extracted protocol syntax information has more comprehensiveness.  
Although our method has made some progress in some aspects, there are still some problems that need to be further solved. One of them is how to accurately determine the fixed value of a specific field, such as the \"Protocol Identity\" field in the Modbus TCP protocol, and the \"Start Bytes\" field in the DNP3.0 protocol, etc. Another challenge is determining the range of data associated with the checksum field. Additionally, we need to find a way to obtain the status information of the protocol. These issues are important directions for our next research. By solving these issues, we can further improve the accuracy and practicality of our method.  
Conceptualization, H.L. and D.Z.; methodology, H.L. and L.Z.; software, L.X.; validation, X.L., S.Y. and X.H.; formal analysis, L.X.; investigation, H.L.; resources, L.Z. and D.Z.; data curation, H.L.; writing--original draft preparation, H.L.; writing--review and editing, L.Z.; visualization, S.Y. and X.H.; supervision, L.X.; project administration, X.L.; funding acquisition, D.Z. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Key R&D Program of China (2023 YFB3107305), in part by the Young Innovation Team of Colleages and Universities in Shandong Province (2021 JK001), in part by the National Natural Science Foundation of China (62172244), in part by the Natural Science Foundation of Shandong Province (ZR2020 YQ06 and ZR2021 MF132), in part by the Innovation Ability Pormotion Project for Small and Medium-sized Technology-based Enterprise of Shandong Province (2022 TSGC2098, 2023 TSGC0150), in part by Talent Research Project of Qilu University of Technology (Shandong Academy of Sciences) (2023 RCKY145), in part by the Pilot Project for Integrated Innovation of Science, Education and Industry of Qilu University of Technology (Shandong Academy of Sciences) (2022 JBZ01-01), in part by the Taishan Scholars Program (tsqn202211210),in part by the Key Research Project of Quancheng Laboratory (QCLZD202303), in part of by the \"20 New Universities\" Project of Jinan City (20233023, 202333045).  
**Informed Consent Statement:** Not applicable.  
Figure 9: Comparison of extraction accuracy and coverage on DCCP protocol.  
Data Availability StatementThe original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.