中图分类号：TP309;TP311.5文献标识码：ADOI:10.19358/j.issn.2097-1788.2024.05.003
引用格式：高伟波,徐炳雪,李仲琴.数据科学的可视化恶意软件分析技术在档案数字化安全管理系统中的应用［J］.网络安全与数据治理，2024，43（5）：18-26.

Application of visual malware analysis technology of data science in archive digital security management system

Abstract： The application of data science′s visual malware analysis technique is an important and innovative technique in the current information security field. This technology combines methods of data analysis, machine learning and visualization, and aims to improve the detection and response capability of potential threats in archive digitization systems. This paper discusses the application of data science-based visual malware analysis technology in archive digitization security management through practice, and constructs a neural network-based malware detection model by combining visual data sets. The advantages of using visual mapping to analyze the detection effect and iterative trend of malware are more efficient and readable than the traditional means of data stripping, and in the process of analysis, it can more quickly and accurately respond to the evolving threats, which provides a strong support for the security of digital archives.

Key words : archive digitization; data science; malware threats; neural networks