Deep Learning in Drebin: Android malware Image Texture Median Filter Analysis and Detection
Luo Shi-Qi, Bo Ni, Jiang Ping, Tian Sheng-wei, Long Yu, Ruijin Wang · KSII Transactions on Internet and Information Systems · 2019
This paper proposes an Image Texture Median Filter (ITMF) to analyze and detect Android malware on Drebin datasets 1 . We design a model of "ITMF" combined with Image Processing of Median Filter (MF) to reflect the similarity of the malware binary file block.At the same time, using the MAEVS (Malware Activity Embedding in Vector Space) to reflect the potential dynamic activity of malware.In order to ensure the improvement of the classification accuracy, the above-mentioned features(ITMF feature and MAEVS feature)are studied to train Restricted Boltzmann Machine (RBM) and Back Propagation (BP).The experimental results show that the model has an average accuracy rate of 95.43%