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DeepVCM: A Deep Learning Based Intrusion Detection Method in VANET

  • Yi Zeng
  • , Meikang Qiu
  • , Dan Zhu
  • , Zhihao Xue
  • , Jian Xiong
  • , Meiqin Liu
  • Xidian University
  • Harrisburg University of Science and Technology
  • Shanghai Jiao Tong University
  • Zhejiang University

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

85 Scopus citations

Abstract

With the rapid development in smart vehicles, the security and privacy issues of the Vehicular Ad-hoc Network (VANET) have drawn significant attention. Devices in an On-Board Unit (OBU) access to the internet through the Vehicular Communication Module (VCM), hence a real-time and accurate intrusion detection method is favored to be applied in VCM. In this paper, we present a Deep Learning (DL) based end-to-end intrusion detection method to automatically detect malware traffic for OBUs. Different from previous intrusion detection methods, our proposed method only requires raw traffic instead of private information features extracted by the human. The performance is compared with previous methods on a public dataset and a simulated real-life VANET dataset. Experimental results show that our method can attain a higher performance with a lower resources requirement.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Big Data Security on Cloud, BigDataSecurity 2019, 5th IEEE International Conference on High Performance and Smart Computing, HPSC 2019 and 4th IEEE International Conference on Intelligent Data and Security, IDS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages288-293
Number of pages6
ISBN (Electronic)9781728100067
DOIs
StatePublished - May 2019
Externally publishedYes
Event5th IEEE International Conference on Big Data Security on Cloud, 5th IEEE International Conference on High Performance and Smart Computing and 4th IEEE International Conference on Intelligent Data and Security, BigDataSecurity/HPSC/IDS 2019 - Washington, United States
Duration: 27 May 201929 May 2019

Publication series

NameProceedings - 5th IEEE International Conference on Big Data Security on Cloud, BigDataSecurity 2019, 5th IEEE International Conference on High Performance and Smart Computing, HPSC 2019 and 4th IEEE International Conference on Intelligent Data and Security, IDS 2019

Conference

Conference5th IEEE International Conference on Big Data Security on Cloud, 5th IEEE International Conference on High Performance and Smart Computing and 4th IEEE International Conference on Intelligent Data and Security, BigDataSecurity/HPSC/IDS 2019
Country/TerritoryUnited States
CityWashington
Period27/05/1929/05/19

Keywords

  • Deep Learning
  • Intrusion Detection
  • OBU
  • VANET
  • VCM

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