关键词: 安卓恶意应用, 检测算法, 卷积神经网络, 朴素贝叶斯方法, 深度学习

Abstract: Android has become the leading operating system in the mobile market. However, the flooding of malicious applications on the Android market is very serious. These malicious applications will bring users great threats. How to detect whether an Android application is a malicious application in advance has become an urgent problem to be solved. In this paper, our scheme improves the original algorithm and proposes a method, which uses both the opcode sequence and the permission information as the characteristics of application and classifies them by convolution neural network (CNN) and naive Bayesian method respectively. This method can detect in advance whether the Android application is a malicious application. The results show that our method works slightly better.

Key words: Android malware, detection algorithm, convolutional neural network, Naive Bayesian method, deep learning