一种基于元信息的 Android 恶意软件检测方法.

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 al gorithm. 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. [ABSTRACT FROM AUTHOR]