Generally speaking, most systems of network traffic identification are based on features. The features may be port numbers, static signatures, statistic characteristics, and so on. The difficulty of the traffic identification is to find the features in the flow data. The process is very time-consuming. Also, these approaches are invalid to unknown protocol. To solve these problems, we propose a method that is based on neural network and deep learning a hotspot of research in machine learning. The results show that our approach works very well on the applications of feature learning, protocol identification, and anomalous protocol detection.
Zhanyi Wang is a data mining researcher with a passion for information security. He hopes to use his experiences in machine learning and data mining to solve problems within this field.
Chuanming Huang is a tech enthusiast, interested in various data mining and parallel computing techniques.
Zhuo Zhang is a team leader with an lab focusing on "Data driven sercurity" in Qihoo360. His team uses big data analytics to find out the threat in the enterprises .He devotes to developing the deep learning system and doing security data research. Until now,his team finds out many threats in the enterprises in China.
Bo Liu is a machine learning & data mining researcher.