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Deep Learning in Drebin: Android malware Image Texture Median Filter Analysis and Detection
( Luo Shi-qi ),( Ni Bo ),( Jiang Ping ),( Tian Sheng-wei ),( Yu Long ),( Wang Rui-jin ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.7
This paper proposes an Image Texture Median Filter (ITMF) to analyze and detect Android malware on Drebin datasetsMedian 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% 1. We design a model of “ITMF” combined with Image Processing of with few false alarms. to Android malicious code, which is significantly higher than 95.2% of without ITMF, 93.8% of shallow machine learning model SVM, 94.8% of KNN, 94.6% of ANN.
The investigation of pH threshold value on the corrosion of steel reinforcement in concrete
Qi Pu,Yan Yao,Ling Wang,Xingxiang Shi,Jingjing Luo,Yifei Xie 사단법인 한국계산역학회 2017 Computers and Concrete, An International Journal Vol.19 No.3
The aim of this study is to investigate the pH threshold value for the corrosion of steel reinforcement in concrete. A method was designed to attain the pH value of the pore solution on the location of the steel in concrete. Then the pH values of the pore solution on the location of steel in concrete were changed by exposing the samples to the environment (CO25%, RH 40%) to accelerate carbonation with different periods. Based on this, the pH threshold value for the corrosion of steel reinforcement had been examined by the methods of half-cell potential and electrochemical impedance spectra (EIS). The results have indicated that the pH threshold value for the initial corrosion of steel reinforcement in concrete was 11.21. However, in the carbonated concrete, agreement among whether steel corrosion was initiatory determined by the detection methods mentioned above could be found.