Identifying the Use of Anonymising Proxies to Conceal Source IP Addresses

Shane Miller, Kevin Curran, Tom Lunney

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
106 Downloads (Pure)

Abstract

The detection of unauthorised users can be problematic for techniques that are available at present if the nefarious actors are using identity hiding tools such as anonymising proxies or Virtual Private Networks (VPNs). This work presents computational models to address the limitations currently experienced in detecting VPN traffic. The experiments conducted to classify OpenVPN usage found that the Neural Network was able to correctly identify the VPN traffic with an overall accuracy of 93.71%. These results demonstrate a significant advancement in the detection of unauthorised user access with evidence showing that there could be further advances for research in this field particularly in the application of business security where the detection of VPN usage is important to an organization.
Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalInternational Journal of Digital Crime and Forensics
Volume13
Issue number6
DOIs
Publication statusPublished (in print/issue) - 1 Nov 2021

Bibliographical note

Publisher Copyright:
© 2021 IGI Global.

Keywords

  • Anonymous proxies
  • Machine learning
  • Security
  • VPNs
  • Virtual private networks

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