基于源代码静态分析技术的Android应用恶意行为检测模型
首发时间:2011-11-03
摘要:目前,基于Linux内核的Android移动终端操作系统面临着大量恶意软件的安全威胁。本文提出一种基于静态分析技术的Android应用恶意行为检测模型,对Android应用反编译后的Java源代码进行词法语法解析、控制流、数据流分析,在此基础上查询引起恶意行为的关键API调用,并对可能使API调用具有恶意性的参数,进行动态污染传播模式对应的关键数据传播分析,进而精确判别并定位到程序怀疑出现恶意行为的关键代码段。
关键词: Android应用恶意行为 静态分析 源代码
For information in English, please click here
Malicious Behavior Detection Model for Android Applications based on Static Analysis of Source Code
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.
Keywords: malicious behavior of Android applications static analysis source code
基金:
论文图表:
引用
No.****
同行评议
共计0人参与
勘误表
基于源代码静态分析技术的Android应用恶意行为检测模型
评论
全部评论0/1000