Behavioral Biometric System Based on Network Traffic Analysis

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Abstract

Network traffic can be analyzed with various methods. In this work we present the hybrid method of analyzing network traffic data combining signature-based and inference-based approaches. We show that there is the potential of building the bio-metric system upon network traffic data and also show that the identification results for 3 persons identification problem reach 0.95 precision and 0.91 recall metric values.
Original languageEnglish
Title of host publicationSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Pages980-982
Number of pages3
ISBN (Electronic)978-1-7281-4401-6
ISBN (Print)978-1-7281-4402-3
DOIs
Publication statusPublished - Oct 2019
EventSIBIRCON 2019 International Multi-Conference - Россия, Новосибирск, Новосибирск, Russian Federation
Duration: 21 Oct 201927 Oct 2019
Conference number: 8
https://sibircon.ieeesiberia.org/

Publication series

NameSIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings

Conference

ConferenceSIBIRCON 2019 International Multi-Conference
Abbreviated titleSIBIRCON 2019
CountryRussian Federation
CityНовосибирск
Period21.10.201927.10.2019
Internet address

Keywords

  • Behaviometrics
  • Biometrics
  • GMMs
  • Hybrid approach
  • Identification
  • Inference-Based approach
  • Network Traffic Analysis
  • Signature-based Approach
  • YAF

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