计算机工程与应用2016，Vol.52Issue(17)：16-23,191,9.DOI:10.3778/j.issn.1002-8331.1509-0091
基于贝叶斯网络的Android恶意行为检测方法
Way of Android malicious behavior detection based on Bayesian net-works
摘要
Abstract
Android is the most popular operating system by far, which has the highest market share. Malicious software based on Android platform also presents explosive growth, but currently there are no effective means, which can detect the Android malicious behavior. In this paper, through analyzing the characteristics of the Android malicious behavior, it uses the machine learning algorithm based on Bayesian networks to detect the Android malicious behavior. Beyond that, this paper extracts the static characteristics of the Android file based on the static analysis method, which has realized the combination of static analysis and the Bayesian network. In the end, through the experiment, it verifies the effectiveness of the Android malicious behavior detection model.关键词
Android/机器学习/特征选择/贝叶斯网络Key words
Android/machine learning/feature selection/Bayesian network分类
信息技术与安全科学引用本文复制引用
张国印,曲家兴,李晓光..基于贝叶斯网络的Android恶意行为检测方法[J].计算机工程与应用,2016,52(17):16-23,191,9.基金项目
黑龙江省国防科学技术研究院项目（No.20150309）；黑龙江省自然科学基金面上项目（No.F201406）；黑龙江省青年科学基金（No.QC2014C067）；黑龙江博士后科研启动基金（No.LBH-Q14056）。 （）
