Vulnerability mining method for industrial control network protocol based on fuzz testing

被引:0
|
作者
Lai Y. [1 ]
Yang K. [1 ]
Liu J. [1 ]
Liu Z. [2 ]
机构
[1] College of Computer Science, Faculty of Information Technology, Beijing University of Technology, Beijing
[2] Institute of Electromechanical Engineering, Beijing Polytechnic, Beijing
关键词
Fuzz testing; Industrial control network protocol; Industrial control private protocol; Industrial control system; Modbus TCP protocol; Protocol features learning; Vulnerability mining;
D O I
10.13196/j.cims.2019.09.014
中图分类号
学科分类号
摘要
To solve the difficulties that traditional vulnerability mining method can't be directly applied to Industrial Control System(ICS), a vulnerability mining method for industrial control network protocol based on fuzz testing was proposed. Protocol feature values were generated by testing cases variation factors for industrial control network protocol, each of which represented a type of ICS vulnerability features. Different test cases were generated by Modbus TCP protocol features and variation factors. Through bypass monitoring method and Modbus TCP protocol features relation between request and response, the difficult problem of determining the validity of testing cases was solved. Aiming at fuzzing industrial control private protocol, the industrial control private protocol tree was established, and the private protocol data set was classified. The private protocol features were learned by probability statistical method of variable byte values, length field learning method, Apriori and Needleman/Wunsch algorithm, which effectively improved the acceptance rate of testing cases for private protocol. Experimental analysis on real industrial control equipment proved that the proposed method could effectively detect vulnerabilities of industrial control public and private protocol. © 2019, Editorial Department of CIMS. All right reserved.
引用
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页码:2265 / 2279
页数:14
相关论文
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