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A Survey on Malicious Domains Detection through DNS Data Analysis

Published:06 July 2018Publication History
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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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  1. A Survey on Malicious Domains Detection through DNS Data Analysis

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            cover image ACM Computing Surveys
            ACM Computing Surveys  Volume 51, Issue 4
            July 2019
            765 pages
            ISSN:0360-0300
            EISSN:1557-7341
            DOI:10.1145/3236632
            • Editor:
            • Sartaj Sahni
            Issue’s Table of Contents

            Copyright © 2018 ACM

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            Publication History

            • Published: 6 July 2018
            • Revised: 1 February 2018
            • Accepted: 1 February 2018
            • Received: 1 August 2017
            Published in csur Volume 51, Issue 4

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