Machine Learning and Multi-dimension Features based Adaptive Intrusion Detection in ICN

Zhihao Li, Jun Wu, Shahid Mumtaz, A. E.M. Taha, Saba Al-Rubaye, Antonios Tsourdos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

As a new network architecture, Information-Centric Networks (ICN) has great advantages in content distribution and can better meet our needs. But it faced with many threats unavoidably. There are four types of attack in ICN: naming related attacks, routing related attacks, caching related attacks and miscellaneous attacks. These attacks will undermine the availability of ICN, the confidentiality and privacy of data. In addition, routers store a large amount of content for the users' request, and it is necessary to protect these intermediate nodes. Since the styles of content stored in nodes are not the same, using a unified set of intrusion detection rules simply will cause a large number of false positives and false negatives. Therefore, every node should perform intrusion detection according to its own characteristics. In this paper, we propose an intrusion detection mechanism to alert for abnormal packets. We introduce a extensive solution using machine learning for attacks in ICN. Moreover, the nodes in this scheme can adapt to the external environment and intelligently detect packets. Simulation on the machine learning algorithm involved prove that the algorithm is effective and suitable for network packets.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728150895
DOIs
Publication statusPublished - 2020 Jun
Externally publishedYes
Event2020 IEEE International Conference on Communications, ICC 2020 - Dublin, Ireland
Duration: 2020 Jun 72020 Jun 11

Publication series

NameIEEE International Conference on Communications
Volume2020-June
ISSN (Print)1550-3607

Conference

Conference2020 IEEE International Conference on Communications, ICC 2020
Country/TerritoryIreland
CityDublin
Period20/6/720/6/11

Keywords

  • ICN
  • defense
  • intrusion detection
  • machine learning

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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