Detection Method of Android Malware Based on Multi-Feature and Stacking Algorithm
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    Abstract:

    As a result of the Android system's popularity, the number of malware on it is increasing rapidly. In this study, a static detection method based on multi-feature and Stacking algorithm is proposed, which can make up the shortcomings of the two aspects, i.e., based on single feature and single algorithm. Firstly, this study uses a variety of feature information to compose the eigenvector, and uses the ensemble learning algorithm of Stacking to combine Logistic, SVM, k-Nearest Neighbor and CART decision trees. Then, classifiers are generated through training samples. The experimental results show that the recognition accuracy is up to 94.05% compared with the single feature and single algorithm, and the classifier has better recognition performance.

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盛杰,刘岳,尹成语.基于多特征和Stacking算法的Android恶意软件检测方法.计算机系统应用,2018,27(2):197-201

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  • Received:May 06,2017
  • Online: February 05,2018
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