一种基于元信息的Android恶意软件检测方法

Android malware detection method based on meta-information

Android应用普遍具有比所属类型更多的功能,需要获取更多的权限,过多的权限可能带来一定的安全隐患。针对这类问题,提出一种基于元信息的Android恶意软件检测方法。首先,通过对Android应用程序描述进行LDA主题提取,实现数据降维,使用K-means聚类算法按照功能类型对应用程序分组;然后,对属于同一功能类型的所有应用程序提取其权限信息,以权限特征为研究对象,使用KNN算法进行Android恶意软件的分类检测。实验结果获得94.81%的平均准确率,证明了方法的有效性和高准确率。

Many Android applications have more functions than their types,and they need to acquire more permissions.Excessive permissions may bring some security risks.To address these issues,this paper proposed an Android malware detection method based on meta information.First,it extracted the LDA theme through the description of Android application,implemented the data dimensionality reduction,and grouped applications by the functional type used the K-means clustering algorithm.Then,for all applications belonging to the same functional type,it extracted their permission information,and took the permission features as the research object,used KNN algorithm to classify and detect the malicious software of Android.The experimental results obtain the average accuracy of 94.81%and prove the validity and high accuracy of the method.