Jie Luo*, Qingbing Ji, Lvlin Ni
Journal on Artificial Intelligence, Vol.4, No.3, pp. 133-142, 2022, DOI:10.32604/jai.2022.031800
Abstract How to quickly and accurately identify applications in VPN encrypted tunnels is a difficult technique. Traditional technologies such as DPI can no longer identify applications in VPN encrypted tunnel. Various VPN protocols make the feature engineering of machine learning extremely difficult. Deep learning has the advantages that feature extraction does not rely on manual labor and has a good early application in classification. This article uses deep learning technology to classify the applications of VPN encryption tunnel based on the SAE-2dCNN model. SAE can effectively reduce the dimensionality of the data, which not only improves the training efficiency of 2dCNN,… More >
Login
Register
