空军工程大学学报2024，Vol.25Issue(4)：94-106,13.DOI:10.3969/j.issn.2097-1915.2024.04.014
基于深度学习的恶意代码检测综述
Review of Malware Detection Based on Deep Learning
摘要
Abstract
Rapid and accurate identification of unknown malware and its variants is one of the important re-search directions in the field of cyberspace security.Based on a brief description of the significant research value of malware detection,the existing deep learning-based malware detection techniques and methods are summarized in consideration of the current situation of domestic and foreign research.Firstly,the tradi-tional detection techniques are sorted out from static,dynamic and hybrid detection methods respectively.Secondly,the malware classification and identification methods based on deep learning are summarized from the malware feature extraction methods based on sequence features,image visualization and data en-hancement.Finally,the technical difficulties and future development trends of malware feature extraction and identification based on deep learning are analyzed and foreseen.关键词
恶意代码/恶意代码分类/恶意代码检测/深度学习/网络空间安全Key words
malware/malware classification/malware detection/deep learning/cyberspace security分类
信息技术与安全科学引用本文复制引用
宋亚飞,张丹丹,王坚,王亚男,郭新鹏..基于深度学习的恶意代码检测综述[J].空军工程大学学报,2024,25(4):94-106,13.基金项目
国家自然科学基金(61806219,61703426,61876189) （61806219,61703426,61876189）
陕西省科学基金(2021JM-226) （2021JM-226）
