android安全静态分析,基于源代码静态分析技术的Android应用恶意行为检测模型

android安全静态分析,基于源代码静态分析技术的Android应用恶意行为检测模型

Malicious Behavior Detection Model for Android Applications based on Static Analysis of Source Code

Lu Cheng

1

路程，(1985-)，男，硕士研究生，主要研究方向：软件安全。

Zhang Miao

1

张淼(1980-)，男，讲师，主要研究方向：软件安全

Xu Guoai

1

徐国爱(1972-)，男，副教授，主要研究方向：软件安全

1、Information Security Center, Beijing University of Posts and Telecommunications

Abstract：Currently, the Android mobile operating system based on Linux kernel is facing a large number of malware threats. It was discussed in the paper about a malicious behavior detection model for Android applications based on a static analysis technique, which analyzes the Java source code decompiled from android applications by lexical and grammar parsing, control flow and data flow analysis.It searches malicious key API calls and analyzes the parameter making the key API calls with malicious by the key data transmission corresponding to the dynamic pollution propagation pattern, it can accurately identify and position the key code suspected to cause malicious behavior.