Identification of abnormal DNS traffic with Hurst parameter

Yıl 2018, Cilt: 6 Sayı: 3, 191 - 197, 31.07.2018

Ali Gezer

https://doi.org/10.17694/bajece.435230

Cited By: 1

Öz

It is a necessity
for effective network management to be aware of the activities taking place on
computer networks. Network managers should always be alarmed about what is
happening now, what might be, or what will be in the future for the sake of
network. To gather information about a computer system or a network, attackers
mostly exploit networking tools to gain some privileges and login systems.
Penetration testers also use these tools to gather information about systems,
but their main concern is to discover the vulnerabilities of the system, and to
find out what kind of measures could be applied to make the system more
resistant to these vulnerabilities. In this study, we propose an abnormal DNS
traffic identification method via utilizing Hurst parameter estimation. To do
so, we employ DNS information gathering tools in Kali Linux to generate
abnormal DNS flows. Then, we estimate its self-similarity degree to compare the
differences between normal DNS traffic flows and abnormal ones. Obtained
results show that abnormal DNS traffic show higher self-similarity degrees.
Another interesting finding is that abnormal DNS traffic shows different
distribution characteristic.

Anahtar Kelimeler

Traffic analysis, DNS protocol, distribution fitting, abnormal traffic detection

Kaynakça

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