FlowletFormer is a BERT-style pre-training model for network traffic that uses flowlet segmentation, field-level tokenization, and two self-supervised objectives, reaching state-of-the-art classification on 7 of 8 public datasets.
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FlowletFormer: Network Behavioral Semantic Aware Pre-training Model for Traffic Classification
FlowletFormer is a BERT-style pre-training model for network traffic that uses flowlet segmentation, field-level tokenization, and two self-supervised objectives, reaching state-of-the-art classification on 7 of 8 public datasets.