A survey on malicious domains detection through DNS data analysis

Yury Zhauniarovich, Issa Khalil, Ting Yu, Marc Dacier

Research output: Contribution to journalArticlepeer-review

127 Scopus citations


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 analysismethods 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.
Original languageEnglish (US)
JournalACM Computing Surveys
Issue number4
StatePublished - Jul 1 2018
Externally publishedYes

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Generated from Scopus record by KAUST IRTS on 2022-09-12


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