基于混合检测的移动智能终端应用程序行为分析系统的研究与实现
esign and Implementation about mobile application behavior analysis based on hybrid detections
随着Android恶意应用程序的不断增多，越来越多的学者开始对Android应用程序的检测方案进行研究。本论文提出并实现了一种基于多种检测方式的Android API调用分析系统。该系统由数据提取模块和数据分析模块组成：数据提取模块分别通过静态分析技术和动态分析技术对手机应用程序进行分析并提取数据；数据分析模块整合两种数据结果，进行预处理，并通过机器学习对未知应用程序进行分类。本论文对静态检测方案和数据分析方案进行测试，测试结果表明该方案能够有效提取数据并分类。
With the increasing number of Android malicious applications, the detection program of Android applications is studing by more and more scholars.In this paper,an analysis system of Android API based on hybrid detections is proposed,which consists of data extraction module and data analysis module. The data extraction module use static analysis and dynamic analysis to achieve the data of Android application.The data analysis module classifies the unknown applications through the collected data and the recognition based on machine learning.The test result of the static analysis system and the data analysis system show that the systems can effectively collect and classify the unknown applications.
唐碧华、张岱帅、范文浩
计算技术、计算机技术
数据安全与计算机安全静态分析混合检测机器学习
ata security and computer securityStatic analysisHybrid detectionmachine learning
唐碧华,张岱帅,范文浩.基于混合检测的移动智能终端应用程序行为分析系统的研究与实现[EB/OL].(2017-12-07)[2025-08-16].http://www.paper.edu.cn/releasepaper/content/201712-96.点此复制
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