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- W2534437878 abstract "With the prosperity of network applications, traffic classification serves as a crucial role in network management and malicious attack detection. The widely used encryption transmission protocols, such as the Secure Socket Layer/Transport Layer Security (SSL/TLS) protocols, leads to the failure of traditional payload-based classification methods. Existing methods for encrypted traffic classification suffer from low accuracy. In this paper, we propose a certificate-aware encrypted traffic classification method based on the Second-Order Markov Chain. We start by exploring reasons why existing methods not perform well, and make a novel observation that certificate packet length in SSL/TLS sessions contributes to application discrimination. To increase the diversity of application fingerprints, we develop a new model by incorporating the certificate packet length clustering into the Second-Order homogeneous Markov chains. Extensive evaluation results show that the proposed method lead to a 30% improvement on average compared with the state-of-the-art method, in terms of classification accuracy." @default.
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- W2534437878 date "2016-06-01" @default.
- W2534437878 modified "2023-09-27" @default.
- W2534437878 title "Certificate-aware encrypted traffic classification using Second-Order Markov Chain" @default.
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- W2534437878 doi "https://doi.org/10.1109/iwqos.2016.7590451" @default.
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