# A Novel Network Protocol Syntax Extracting Method for Grammar-Based Fuzzing
## 1 Introduction  
Network protocols are a set of rules, standards, or conventions established for data exchange in a computer network. Network protocols consist of three elements, namely semantics, syntax, and timing, wherein the syntax is the structure and format of the exchanging data and control information [1]. It plays an important role in the process of functionality/security testing of network communication software or hardware equipment [2, 3]. For example, when conducting fuzzing on network communication software, network protocol syntax information ensures the validity of generated test cases, thereby enhancing fuzzing efficiency [4, 5, 6]. However, the complexity and diversity of network protocols present significant challenges to understand and process them thoroughly. Consequently, there is an urgent need to rapidly and comprehensively extract syntax information from a wide array of different network protocols. This has emerged as a critical research area within the realms of network security and software testing [7, 8]. Currently, methods for extracting network protocol syntax information can be divided into two categories, manual method and automated methods. The manual method usually relies on experts to manually extract protocol syntax information from protocol specifications, it has the advantage of high accuracy. Experts can accurately define key features of protocol syntax based on domain knowledge [9]. However, this method has a low degree of automation, the extraction process is usually time-consuming and labor-intensive. At the same time, the manual method has poor versatility and makes it difficult to process plenty of different protocols. Automated methods include methods based on software reverseengineering, methods based on traffic analysis, and artificial intelligence methods based on protocol specifications [10]. The software reverse engineering method extracts the syntax information of the network protocol by analyzing the binary data flow of the protocol processing software [11; 12; 13]. This method is usually applied to the analysis of unknown protocols, and researchers need to have perfect knowledge and skills in assembly language and binary analysis [14]. Traffic-analysis-based methods utilize network communication data flows to obtain network protocol syntax knowledge, but there are challenges in improving information comprehensiveness. Besides, encrypted traffic makes data unreadable thus further limiting the analysis of protocol syntax [15; 16; 17]. Artificial intelligence methods use machine learning or natural language processing technology to extract structured information from text documents by learning protocol grammar rules [18; 19; 20]. By using special pre-made protocol specification data sets for model training, the machine learning model can learn the underlying patterns of protocol syntax and achieve a certain degree of automation and generality. However, the accuracy of this method is affected by many factors, including the quality of the training data, the selection of features, and the complexity of the model. Especially when facing new or unknown protocols, the applicability of this method is low. In addition, obtaining high-quality training data is also one of the challenges faced by artificial intelligence methods [21]. Considering the diversity and complexity of network protocols, the manual method definitely has difficulty in extracting protocol syntax information arbitrarily and quickly. At the same time, although artificial intelligence methods have made certain progress in dealing with these problems, they usually have an unsatisfactory performance in result completeness and they are often designed for specific protocol formats, which limits their versatility. In this context, designing an automated and universal method for extracting network protocol syntax information has become an important and challenging research issue.