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Malware Detection in TLS Communication
Kapišinský, Marián ; Ryšavý, Ondřej (oponent) ; Matoušek, Petr (vedoucí práce)
This master's thesis demonstrates that encrypted malware communication can still be detected in the network traffic despite the differences between the encrypted communication of the ever-evolving malware and benign processes slowly diminishing. The detection relies purely on data extracted from the unencrypted portions of the TLS protocol. The data is then analyzed using random forests and isolation forests. The work demonstrates that both models perform well with only a small number of inaccurate classifications. The two models also show similar results in a real-world deployment.

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