网络钓鱼
计算机科学
服务器
实施
互联网
恶意软件
财产(哲学)
计算机安全
万维网
人工智能
入侵检测系统
数据科学
机器学习
僵尸网络
领域(数学分析)
哲学
认识论
程序设计语言
作者
Kang Li,Xiangzhan Yu,Jiujin Wang
出处
期刊:Communications in computer and information science
日期:2021-07-19
卷期号:: 152-162
被引量:2
标识
DOI:10.1007/978-3-030-78621-2_12
摘要
AbstractMalicious domains are one of the critical manifestations of cyber security attacks, severely posing threats to people’s privacy and property by providing malicious services (such as spam servers, phishing websites, and C&C servers) to Internet users. Therefore, researches on technology of malicious domains detection have also attracted much attention. Existing methods show significant differences in data sources and method implementations. In this paper, we conduct a retrospective analysis on them, and divide data into two types namely DNS data and DGA data. Different data sources correspond to different data forms and loaded information, so that researchers need to adopt appropriate methods to detect malicious domains by using such information. The detection methods are divided into four types. We describe general detection framework for each type of approach, and make an outlook for future research directions.KeywordsMalicious domains detectionDGADomain Name System
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