Fine-grained Android Malware Detection based on Deep Learning

作者：Dongfang Li, Zhaoguo Wang, Yibo Xue · 年份：2018 · DOI：10.1109/cns.2018.8433204 · 被引用次数：57 · 研究领域：Advanced Malware Detection Techniques、Network Security and Intrusion Detection、Software Testing and Debugging Techniques

Android smartphone users have been suffering from the security problems these years. There is a serious threat to the network security and privacy brought by the mobile malware. In this paper, we use the deep-learning-based method to detect Android malware and implement an automatic detection engine to detect the families of malicious applications. The results of the evaluation show that the engine can detect 97% of the malware at 0.1% false positive rate (FPR) when detecting the fine-grained malware families.