Paper: Encrypted Traffic Classification Through Deep Learning (Yupeng Lei, Jun Wu, Xudong Sun, Liang Zhang, Qin Wu)
slides-mtenws-paper-encrypted-traffic-classification-through-deep-learning-lei-wu-sun-zhang-wu-00

Quickly and accurately classify applications is important for network congestion control and network service assurance. However with the increased usage of data encryption, privacy enhancing technologies, it became difficult to obtain metadata or sample labels for private enterprise applications. This position papers discusses encrypted traffic classification through deep learning technology. A flow-based classification mechanism is proposed, which only relies on the statistical characteristics of packets, such as time series characteristics, 5 tuple information for feature extraction.