Detecting DNS hijacking by using NetFlow data

Martin Fejrskov Andersen, Jens Myrup Pedersen, Emmanouil Vasilomanolakis

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)
167 Downloads (Pure)

Abstract

DNS hijacking represents a security threat to users because it enables bypassing existing DNS security measures. Several malware families exploit this by changing the client DNS configuration to point to a malicious DNS resolver. Following the assumption that users will never actively choose to use a resolver that is not well-known, our paper introduces the idea of detecting client-based DNS hijacking by classifying public resolvers based on whether they are well-known or not. Furthermore, we propose to use NetFlow-based features to classify a resolver as well-known or malicious. By characterizing and manually labelling the 405 resolvers seen in four weeks of NetFlow data from a national ISP, we show that classification of both well-known and malicious servers can be made with an AUROC of 0.85.
Original languageEnglish
Title of host publication2022 IEEE Conference on Communications and Network Security (CNS)
Number of pages8
PublisherIEEE
Publication date14 Nov 2022
Pages273-280
ISBN (Print)978-1-6654-6256-3
ISBN (Electronic)978-1-6654-6255-6
DOIs
Publication statusPublished - 14 Nov 2022
Event2022 IEEE Conference on Communications and Network Security (CNS) - Austin, United States
Duration: 3 Oct 20225 Oct 2022

Conference

Conference2022 IEEE Conference on Communications and Network Security (CNS)
Country/TerritoryUnited States
CityAustin
Period03/10/202205/10/2022

Bibliographical note

Funding Agency:
Telenor A/S and Innovation Fund Denmark

Keywords

  • NetFlow
  • IPFix
  • DNS
  • hijacking
  • malware

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