首页> 外文期刊>Neurocomputing >Effective method for detecting malicious PowerShell scripts based on hybrid features
【24h】

Effective method for detecting malicious PowerShell scripts based on hybrid features

机译:基于混合功能检测恶意PowerShell脚本的有效方法

获取原文
获取原文并翻译 | 示例

摘要

At present, network attacks are rampant in the Internet world, and the attack methods of hackers are changing steadily. PowerShell is a programming language based on the command line and.NET framework, with powerful functions and good compatibility. Therefore, hackers often use PowerShell malicious scripts to attack the victims in APT attacks. When these malicious PowerShell scripts are executed, hackers can control the victim & rsquo;s computer or leave a backdoor on their computers. In this paper, a detection model of malicious PowerShell scripts based on hybrid features is proposed, we analyzed the differences between malicious and benign samples in text characters, functions, tokens and the nodes of the abstract syntax tree. Firstly, the script of PowerShell is embedded by FastText. Then the textual features, token features and the nodes features of PowerShell code extracted from the abstract syntax tree are added. Finally, the hybrid features of scrips will be classified by a Random Forest classifier. In the experiment, the malicious scripts are inserted into the benign scripts to weaken the features of the malicious samples in the level of abstract syntax tree nodes and tokens, which makes the scripts more complex. Even in such a complex data set, the proposed model which is based on hybrid features still achieves an accuracy of 97.76% in fivefold cross-validation. Moreover, the accuracy of this proposed model on the original scripts is 98.93%, which means that the proposed model has the ability to classify complex scripts.(c) 2021 Elsevier B.V. All rights reserved.
机译:目前,网络攻击在互联网世界中猖獗,黑客攻击方法正在稳步变化。 PowerShell是一种基于命令行和网络框架的编程语言,具有强大的功能和良好的兼容性。因此,黑客经常使用PowerShell恶意脚本来攻击APT攻击中的受害者。当执行这些恶意PowerShell脚本时,黑客可以控制受害者和rsquo; s计算机或在计算机上留下后门。在本文中,提出了一种基于混合功能的恶意PowerShell脚本的检测模型,我们分析了文本字符,函数,令牌和抽象语法树的节点中的恶意和良性样本之间的差异。首先,通过FastText嵌入PowerShell的脚本。然后,添加了从抽象语法树中提取的PowerShell代码的文本功能,令牌功能和节点功能。最后,船舶的混合特征将由随机林分类器分类。在实验中,将恶意脚本插入良性脚本中,以削弱流行语法树节点和令牌等级中恶意样本的功能,这使得脚本更加复杂。即使在这种复杂的数据集中,基于混合特征的所提出的模型仍然在五倍交叉验证中实现了97.76%的精度。此外,原始脚本上提出模型的准确性为98.93%,这意味着所提出的模型能够对复杂脚本进行分类。(c)2021 Elsevier B.v.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号