A unified host-based intrusion detection framework using spark in cloud

Ming Liu, Zhi Xue, Xiangjian He

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

1 Citation (Scopus)

Abstract

The host-based intrusion detection system (HIDS) is an essential research domain of cybersecurity. HIDS examines log data of hosts to identify intrusive behaviors. The detection efficiency is a significant factor of HIDS. Traditionally, HIDS is often installed with a standalone mode. Training detection engines with a large amount of data on a single physical computer with limited computing resources may be time-consuming. Therefore, this paper offers a unified HIDS framework based on Spark and deployed in the Google cloud. The framework includes a unified machine learning pipeline to implement scalable and efficient HIDS.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
EditorsGuojun Wang, Ryan Ko, Md Zakirul Alam Bhuiyan, Yi Pan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages97-103
Number of pages7
ISBN (Electronic)9781665403924
DOIs
Publication statusPublished - Dec 2020
Externally publishedYes
Event19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 - Guangzhou, China
Duration: 29 Dec 20201 Jan 2021

Publication series

NameProceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

Conference

Conference19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
Country/TerritoryChina
CityGuangzhou
Period29/12/201/01/21

Keywords

  • Intrusion detection
  • Scalable
  • System call

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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