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The explosive amount of Android malware have threatened the security of legitimate users. In Recent years, with the development of the neural network, more and more research is focusing on detecting malware based on the neural network. Where, most of these techniques are depending on the complex feature engineering process and have a resource and time expensive classification neural network. In this paper, we propose a novel lightweight convolution neural network model, ConvDroid, with thedblp:journals/ajiips/WuX19 fatcat:3foe6cioibeqnptbxs35xxlqf4