Review of Android Malware Detection Based on Deep Learning

IEEE Access

Yaping Chi¹  Zhiqiang Wang¹  Qian Liu¹ 

[1] Department of Cyberspace Security, Beijing Electronic Science and Technology Institute, Beijing, China;

关键词: Android;    malware;    deep learning;    review;   

DOI  :  10.1109/ACCESS.2020.3028370

来源: DOAJ

【 摘 要 】

At present, smartphones running the Android operating system have occupied the leading market share. However, due to the Android operating system's open-source nature, Android malware has increased dramatically. Malware can steal user privacy and even maliciously charge fees and steal funds. It has posed a severe threat to cyberspace security because traditional detection methods have many limitations. With the widespread application of deep learning in recent years, the method of detecting Android malware using deep learning has gradually attracted widespread attention from scholars at home and abroad. Although scholars have researched Android malware detection using deep learning, there is currently a lack of a detailed and comprehensive introduction to malware detection's latest research results based on deep learning. In order to solve this problem, this study analyzes and summarizes the latest research results by investigating a large number of the latest domestic and international academic papers, summarizing malware detection architecture and detection schemes, and analyzing existing problems and challenges. This review will help researchers better understand the research status and future research directions in this field.

【 授权许可】

Unknown