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DNS tunneling techniques are often used for malicious purposes but networksecurity mechanisms have struggled to detect these. Network forensic analysishas thus been used but has proved slow and effort intensive as NetworkForensics Analysis Tools struggle to deal with undocumented or new networktunneling techniques. In this paper we present a method to aid forensicanalysis through automating the inference of protocols tunneled within DNStunneling techniques. We analyze the internal packet structure of DNS tunnelingtechniques and characterize the information entropy of different networkprotocols and their DNS tunneled equivalents. From this, we present ourprotocol prediction method that uses entropy distribution averaging. Finally weapply our method on a dataset to measure its performance and show that it has aprediction accuracy of 75%. Our method also preserves privacy as it does notparse the actual tunneled content, rather it only calculates the informationentropy.

Entropy-based Prediction of Network Protocols in the Forensic Analysis of DNS Tunnels