Generating network intrusion detection dataset based on real and encrypted synthetic attack traffic

Andrey Ferriyan, Achmad Husni Thamrin, Keiji Takeda, Jun Murai

Research output: Contribution to journalArticlepeer-review

Abstract

The lack of publicly available up-to-date datasets contributes to the difficulty in evaluating intrusion detection systems. This paper introduces HIKARI-2021, a dataset that contains encrypted synthetic attacks and benign traffic. This dataset conforms to two requirements: the content require-ments, which focus on the produced dataset, and the process requirements, which focus on how the dataset is built. We compile these requirements to enable future dataset developments and we make the HIKARI-2021 dataset, along with the procedures to build it, available for the public.

Original languageEnglish
Article number7868
JournalApplied Sciences (Switzerland)
Volume11
Issue number17
DOIs
Publication statusPublished - 2021 Sep 1

Keywords

  • Encrypted network traffic
  • Https
  • Network intrusion datasets
  • Network intrusion detection system
  • Tls

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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