Profiling malicious domain by multidimensional features

Du Cheng, Zhenyan Liu, Pengfei Zhang, Yifei Zeng, Jia Cui, Lei Kong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

In malicious domain detection research, one of the most critical challenges is how to construct features which can profile malicious domain. At present, different studies constructed the features of malicious domain from different points or granularity levels respectively. In order to have an insight into these features involved in the existing studies, this paper specifically provides a comprehensive survey and summary. In this paper, we first introduce briefly the harmfulness of malicious domain and the typical malicious behavior based on malicious domain. And then we focus on profiling malicious domain by means of static features and dynamic features. In the end, we also forecast the future of profiling malicious domain.

Original languageEnglish
Title of host publicationProceedings - 2018 International Conference on Robots and Intelligent System, ICRIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages489-495
Number of pages7
ISBN (Electronic)9781538665800
DOIs
Publication statusPublished - 11 Jul 2018
Event2018 International Conference on Robots and Intelligent System, ICRIS 2018 - Changsha, China
Duration: 26 May 201827 May 2018

Publication series

NameProceedings - 2018 International Conference on Robots and Intelligent System, ICRIS 2018

Conference

Conference2018 International Conference on Robots and Intelligent System, ICRIS 2018
Country/TerritoryChina
CityChangsha
Period26/05/1827/05/18

Keywords

  • DNS
  • Dynamic features
  • Malicious domain detection
  • Malware
  • Static features

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