Entropy-based IoT devices identification

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

Abstract

The Internet of Things is now part of everyday life and there has been a wide range of novel IoT applications collecting cyber-physical data and providing information on the environment. As it is expected that the IoT traffic will count for a major part of the Internet traffic, it is essential to characterize the IoT traffic and to identify each device, and especially in the case of cyberattacks. In this paper, we present a new method to identify IoT devices based on traffic entropy. We compute the entropy values of traffic features and we rely on Machine Learning algorithms to classify the traffic. Our method succeeds in identifying devices under various network conditions with performances up to 94% in all cases. Our method is also robust to unpredictable network behavior with anomalies spreading into the network.

Original languageEnglish
Title of host publicationAPNOMS 2020 - 2020 21st Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationTowards Service and Networking Intelligence for Humanity
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages73-78
Number of pages6
ISBN (Electronic)9788995004388
DOIs
Publication statusPublished - 2020 Sep
Event21st Asia-Pacific Network Operations and Management Symposium, APNOMS 2020 - Daegu, Korea, Republic of
Duration: 2020 Sep 222020 Sep 25

Publication series

NameAPNOMS 2020 - 2020 21st Asia-Pacific Network Operations and Management Symposium: Towards Service and Networking Intelligence for Humanity

Conference

Conference21st Asia-Pacific Network Operations and Management Symposium, APNOMS 2020
CountryKorea, Republic of
CityDaegu
Period20/9/2220/9/25

Keywords

  • Anomaly
  • Entropy
  • Identification
  • IoT
  • Traffic Analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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