Research on Fuzz Testing Optimization Technology for Power Internet of Things Protocol

• Published in: 2023 IEEE 13th International Conference on Electronics Information and Emergency Communication (ICEIEC) pp. 213 - 217
• Main Authors: Liu, Donglan, Wang, Rui, Chang, Yingxian, Chen, Jianfei, Liu, Xin, Zhang, Fangzhe, Yao, Honglei, Zhang, Hao, Sun, Lili, Yu, Hao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.07.2023
• Subjects: Behavioral sciences; Collaboration; fuzz testing; fuzz testing optimization technology; Fuzzing; power Internet of things protocol; Protocols; Scheduling; Search problems; Symbols; vulnerability detection
• ISSN: 2377-844X
• DOI: 10.1109/ICEIEC58029.2023.10200674

In this paper, the fuzz testing optimization technology for power Internet of Things protocol is studied to improve the accuracy of vulnerability detection for power Internet of Things protocol. The automatic message generation technology of electric Internet of Things protocol based on symbol execution is proposed to solve the adaptation problem and path explosion problem of network protocol symbol execution. By adopting different search strategies and solving optimization to generate the initial seed of protocol message efficiently and with high quality, the preparation cost of fuzz testing is greatly reduced. A fuzz testing technique based on multi-party cooperation is proposed to analyze the execution flow of program blocks caused by message exchange between multiple programs. By designing a new coverage model considering program interaction, the collaborative interaction between different participants of the protocol is combined into coverage calculation, which reflects the overall execution process of complex protocol. We focus on the fuzz testing optimization technology for electric Internet of Things protocol. A fuzz testing optimization technique based on protocol state is proposed to monitor the changes of key state variables in protocol implementation. A new seed scheduling and change algorithm is designed for state change sequence, and a multi-party coordination scenario is combined to guide protocol fuzz testing. A fuzz testing optimization technique based on seed grouping is proposed. In view of the large differences in the seeds of power Internet of Things protocol messages, an efficient seed and execution path similarity calculation method, seed grouping method and a variety of fuzz testing optimization algorithms based on grouping are proposed to group seeds online. At the same time, the fuzz testing is optimized according to the characteristics of each class.