Institute of Electrical & Electronic Engineers
In this paper, the authors present a novel traffic classification scheme to improve classification performance when few training data are available. In the proposed scheme, traffic flows are described using the discretized statistical features and flow correlation information is modeled by Bag-of-Flow (BoF). They solve the BoF-based traffic classification in a classifier combination framework and theoretically analyze the performance benefit. Furthermore, a new BoF-based traffic classification method is proposed to aggregate the Naive Bayes (NB) predictions of the correlated flows.