中圖分類號：TP393
文獻標識碼：A
DOI:10.19358/j.issn.2097-1788.2023.06.011
引用格式：戚臻彥，孫永清.基于隨機森林的命令混淆繞過檢測研究［J］.網絡安全與數據治理，2023，42（6）：66-70.

Research on command obfuscation bypass detection based on random forest algorithm

Abstract： The "command filtering" function in operation and maintenance security devices can only filter malicious code in the blacklist, and cannot effectively identify and prevent the use of special methods to bypass this function. To address this problem, this paper proposes an algorithm based on random forest, which can accurately identify command execution statements containing malicious code. Firstly, this paper introduces four methods of command obfuscation bypass, which are used to evade keywords in the blacklist and perform command execution. Then, in order to solve these risks, the command obfuscation code is taken into account in the feature selection stage of the model, and various features are used to train and adjust the weights of the random forest model, so as to improve the recognition rate and accuracy of the model detection for adding command obfuscation attacks. The experimental results show that the method proposed in this paper can timely identify and deal with command obfuscation attacks, thus better ensuring the secure operation of servers.

Key words : command obfuscation; operation and maintenance management equipment; random forest; network security