A Survey on Malicious Domains Detection through DNS Data Analysis

TL;DR

This survey comprehensively reviews various DNS data analysis techniques for detecting malicious domains, categorizing approaches by data sources, analysis methods, and evaluation strategies, and discusses challenges for future research.

Contribution

It provides a systematic classification and critical analysis of existing DNS-based malicious domain detection methods, highlighting their advantages and limitations.

Findings

Different approaches vary in data sources and analysis techniques.

Evaluation methodologies differ significantly across studies.

Identified key challenges for improving DNS-based detection.

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 paper, we perform such an analysis. In order 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.