Markov chain fingerprinting to classify encrypted traffic
Published: Apr 1, 2014
Abstract
In this paper, we propose stochastic fingerprints for application traffic flows conveyed in Secure Socket Layer/Transport Layer Security (SSL/TLS) sessions. The fingerprints are based on first-order homogeneous Markov chains for which we identify the parameters from observed training application traces. As the fingerprint parameters of chosen applications considerably differ, the method results in a very good accuracy of application...
Paper Details
Title
Markov chain fingerprinting to classify encrypted traffic
Published Date
Apr 1, 2014
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