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Transmission control protocol (TCP) congestion control is one of the keytechniques to improve network performance. TCP congestion control algorithmidentification (TCP identification) can be used to significantly improvenetwork efficiency. Existing TCP identification methods can only be applied tolimited number of TCP congestion control algorithms and focus on wirednetworks. In this paper, we proposed a machine learning based passive TCPidentification method for wired and wireless networks. After comparing amongthree typical machine learning models, we concluded that the 4-layers LongShort Term Memory (LSTM) model achieves the best identification accuracy. Ourapproach achieves better than 98% accuracy in wired and wireless networks andworks for newly proposed TCP congestion control algorithms.

Passive TCP Identification for Wired and WirelessNetworks: A Long-Short Term Memory Approach