Intelligent Mechanisms for Extracting Signs of File Modification in Dynamic Virus Analysis

IF 0.5 Q4 AUTOMATION & CONTROL SYSTEMS AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-03-14 DOI:10.3103/S0146411624700810
S. G. Fomicheva, O. D. Gayduk
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Abstract

This paper proposes machine-learning pipelines that allow automatically generating the relevant feature spaces for virus detectors, detect the presence of viral modifications in JS-files and scripts in real time, and interpret and visualize the automatically obtained machine solution. It is shown that the best quality metrics will be demonstrated by models of an abstract syntactic tree using binary classifiers based on ensembles of decision trees. An explanation of the solution automatically generated by the virus detector is demonstrated.

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动态病毒分析中提取文件修改迹象的智能机制
本文提出了机器学习管道,可以自动生成病毒检测器的相关特征空间,实时检测js文件和脚本中是否存在病毒修改,并对自动获得的机器解决方案进行解释和可视化。结果表明,使用基于决策树集成的二元分类器的抽象语法树模型将展示最佳质量度量。演示了病毒检测器自动生成的解决方案的说明。
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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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