App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 5

MSIEFuzzer: fuzz testing method of industrial control protocol based on multi-scale information entropy

Liu Mingrui1,2
Zong Xuejun1,2
He Kan1,2
Lian Lian1,2
Shi Hongyan1,2
Sun Yifei1,2
Ning Bowei2,3
1. College of Information Engineering, Shenyang Chemical University, Shenyang Liaoning 110142, China
2. Liaoning Key Laboratory of Information Security for Petrochemical Industry, Shenyang Liaoning 110142, China
3. College of Artificial Intelligence, Shenyang University of Technology, Shenyang Liaoning 110870, China
DOI: 10.19734/j.issn.1001-3695.2025.09.0373

Abstract

This paper proposed a Multi-Scale Information Entropy (MSIE) based fuzz testing method to address high redundancy and blind mutation in industrial control protocol test cases. The method utilized a policy-optimized generative adversarial network (WSGAN) to learn protocol format specifications. The generator training integrated Proximal Policy Optimization (PPO) with Monte Carlo Tree Search (MCTS) , achieving dynamic optimization and stable policy updates. MSIE divides protocol fields into fixed and variable categories, while the WRD algorithm computes test sample similarity. Based on field division results, the method performs targeted mutation on high-similarity samples to reduce redundancy. This study developed the MSIEFuzzer framework and conducted experimental verification at an industrial scenario drill range in the Key Laboratory of Information Security of the Petrochemical Industry in Liaoning Province. Experimental results demonstrated that MSIEFuzzer achieved higher acceptance rate and greater diversity compared to WGANFuzzer, GANFuzzer and PeachFuzzer, improving abnormal trigger rates by 19.35%, 42.33% and 70.03% respectively. These findings confirm the framework's validity and universality.

Foundation Support

辽宁省科技重大专项项目(辽科办发[2025]77号(3)-1)
辽宁省应用基础研究计划项目(辽科办发[2025]64号(12)
辽宁省科技重大专项项目(2024JH1/11700049)
辽宁省自然科学基金资助项目(2023-MSLH-273)
辽宁省科学技术计划项目(2023JH1/10400082)
辽宁省科技创新平台建设计划项目(辽科发[2022]36号)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.09.0373
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 5

Publish History

[2026-01-13] Accepted Paper

Cite This Article

刘明睿, 宗学军, 何戡, 等. MSIEFuzzer：基于多尺度信息熵的工业控制协议模糊测试方法 [J]. 计算机应用研究, 2026, 43 (5). (2026-01-20). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0373. (Liu Mingrui, Zong Xuejun, He Kan, et al. MSIEFuzzer: fuzz testing method of industrial control protocol based on multi-scale information entropy [J]. Application Research of Computers, 2026, 43 (5). (2026-01-20). https://doi.org/10.19734/j.issn.1001-3695.2025.09.0373. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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