摘要
针对安卓系统非正常程序较多的现状,提出一种新的检测方法,结合了应用程序分类以及系统调用法,目的是提高安卓系统非正常程序检测的准确性。计算分类的数据采自谷歌商店,非正常程序样本采自安卓病毒共享库,通过系统调用值和阈值的计算对比,判断实验样本的正常性。实验结果表明:本文提出的方法能够准确检测出安卓系统中的非正常程序,有一定的推广价值。
Aiming at the current situation that there are many abnormal programs in Android system,a new detection method is proposed,which combines application classification and system call method.The purpose is to improve the accuracy of the detection of abnormal programs in Android system.The classified data were collected from Google Store,and the abnormal program samples were collected from Android virus shared library.The normality of the experimental samples was judged by comparing the system call values and thresholds.The experimental results show that the method proposed in this paper can accurately detect abnormal programs in Android system,and has certain popularization value.
作者
李清炀
LI Qing-yang(School of Criminal Justice/East China University of Political Science and Law,Shanghai 201620,China)
出处
《山东农业大学学报(自然科学版)》
北大核心
2019年第1期150-153,共4页
Journal of Shandong Agricultural University:Natural Science Edition
关键词
安卓系统
非正常程序
检测
SMO
Android system
abnormal procedures
detection
SMO