RLCS: A Classification System Based on Random Forest and Logistic Regression for Hybrid Zero-day Traffic

Traffic classification has attracted public attention for a long time because of its essential role in network management. However, the presence of zero-day traffic, network traffic generated by previously unknown applications, leads to a significant reduction in the practicability and effectiveness of conventional traffic classification schemes. This poster innovatively proposes a traffic classification scheme named RLCS to accomplish the high accurate traffic classification task in hybrid zero-day traffic. The evaluations with real-world traffic verify the effectiveness and broad applicability of RLCS.