Detecting DNS hijacking by using NetFlow data

Martin Fejrskov, Jens Myrup Pedersen, Emmanouil Vasilomanolakis

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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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 publicationProceedings of 10th IEEE Conference on Communications and Network Security
Number of pages8
PublisherIEEE
Publication date2022
ISBN (Print)978-1-6654-6256-3
DOIs
Publication statusPublished - 2022
Event10th annual IEEE Conference on Communications and Network Security - Hilton Austin, Austin, United States
Duration: 3 Oct 20225 Oct 2022
https://cns2022.ieee-cns.org/

Conference

Conference10th annual IEEE Conference on Communications and Network Security
LocationHilton Austin
Country/TerritoryUnited States
CityAustin
Period03/10/202205/10/2022
Internet address

Keywords

  • NetFlow
  • IPFix
  • DNS
  • Hijacking
  • Malware

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