Droid-Sec: Deep Learning in Android Malware Detection

作者：Yuan, Zhenlong^*; Lu, Yongqiang; Wang, Zhaoguo; Xue, Yibo

来源：Computer Communication Review, 2014, 44(4): 371-372.

DOI：10.1145/2740070.2631434

• Android malware
• deep learning
• detection

As smart:phones and mobile devices are rapidly becoming indispensable for many network users, mobile malware has become a serious threat in the network security and privacy. Especially on the popular Android platform, many malicious apps are hiding in a large number of normal apps, which makes the malware detection more challenging. In this paper, we propose a ML-based method that utilizes more than 200 features extracted from both static analysis and dynamic analysis of Android app for malv -are detection. The comparison of modeling results demonstrates that the deep learning technique is especially suitable for Android mahvare detection and can achieve a high level of 96% accuracy with real-world Android application sets.

• 出版日期2014-10
• 单位清华大学; 哈尔滨工业大学; 深圳清华大学研究院