Abstract
The JA3 algorithm for fingerprinting TLS client traffic has become a popular additional tool in the tool set of network security professionals. The pre-hash value of the JA3 fingerprint lists parameter values from the TLS handshake supported by the TLS client. In this paper we present two different machine learning methods for identifying the endpoint application from TLS traffic based on the JA3 pre-hash string. Both methods were able to identify applications from Mozilla in our sample set, but had more variation with other applications. The methods can be used for improving network security accuracy.
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