A Survey on Malicious Domains Detection through DNS Data Analysis

The work

AuthorsYury Zhauniarovich; Issa Khalil; Ting Yu; Marc Dacier
Editors
Typearticle
Year2019
Citekeyzhauniarovich2019survey

Where it appeared

Published inACM Computing Surveys
Volume51
Issue4
Pages1--36

Identifiers

arXiv1805.08426
DOI10.1145/3191329

Abstract

Malicious domains are one of the major resources required for adversaries to run attacks over the Internet. Due to the important role of the Domain Name System (DNS), extensive research has been conducted to identify malicious domains based on their unique behavior reflected in different phases of the life cycle of DNS queries and responses. Existing approaches differ significantly in terms of intuitions, data analysis methods as well as evaluation methodologies. This warrants a thorough systematization of the approaches and a careful review of the advantages and limitations of every group. In this article, we perform such an analysis. To achieve this goal, we present the necessary background knowledge on DNS and malicious activities leveraging DNS. We describe a general framework of malicious domain detection techniques using DNS data. Applying this framework, we categorize existing approaches using several orthogonal viewpoints, namely (1) sources of DNS data and their enrichment, (2) data analysis methods, and (3) evaluation strategies and metrics. In each aspect, we discuss the important challenges that the research community should address in order to fully realize the power of DNS data analysis to fight against attacks leveraging malicious domains.

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Added2026-08-10 00:00 UTC
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Cite it as

@article{zhauniarovich2019survey,
  title        = {A Survey on Malicious Domains Detection through DNS Data Analysis},
  author       = {Yury Zhauniarovich and Issa Khalil and Ting Yu and Marc Dacier},
  year         = {2019},
  journal      = {ACM Computing Surveys},
  volume       = {51},
  number       = {4},
  pages        = {1--36},
  eprint       = {1805.08426},
  doi          = {10.1145/3191329},
}

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