Method of application classification in Tor anonymous communication flow
A technology for anonymous communication and application classification, applied in the research field of anonymous communication and traffic analysis, it can solve problems such as abuse and network security threats, and achieve the effect of fast running speed, less network load and good classification effect.
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[0024] This method mainly solves the problem of obtaining upper-layer application type information in Tor anonymous communication traffic, and involves related technologies such as feature selection, sample preprocessing, and traffic modeling. This method first uses Tor's data packet scheduling mechanism to define the concept of flow bursts, and uses the volume and direction of flow bursts as classification features. Then the data samples were preprocessed based on the K-means clustering algorithm and the multiple sequence alignment algorithm, and the overfitting and length inconsistencies of the data samples were solved by numerical symbolization and gap insertion. Finally, using the Profile Hidden Markov Model to model the uplink and downlink Tor anonymous communication traffic of different applications, a heuristic algorithm is proposed to quickly establish the Profile Hidden Markov Model. In the specific classification, the characteristics of the network traffic to be clas...
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