DNS Tunneling Detection Using Feedforward Neural Network

Yakov Bubnov
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Yakov Bubnov: Belarusian State University of Informatics and Radioelectronics

European Journal of Engineering and Technology Research, 2018, vol. 3, issue 11, 16-19

Abstract: This paper addresses a problem of detecting Domain Name System (DNS) tunneling in a computer network. Unauthorized data transfer exploits DNS tunneling technique to conceal network activity in a regular DNS traffic. Contemporary intrusion prevention equipment does not provide reasonable protection from sensitive information stealing. Given the DNS queries from both legitimate and adversary clients this paper proposes a machine-learning method of distinguishing tunneling strategies. More precisely, it describes a multi-label model of feedforward neural network that classifies some of well-known tunneling strategies counting legitimate traffic. The paper contains analysis of classification quality and accuracy of the developed model.

Keywords: Data Exfiltration; Domain Name System; Neural Network; Tunneling Detection (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:3:y:2018:i:11:id:60963

DOI: 10.24018/ejeng.2018.3.11.963

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