抄録

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.

本文言語English
ホスト出版物のタイトルAPNOMS 2020 - 2020 21st Asia-Pacific Network Operations and Management Symposium
ホスト出版物のサブタイトルTowards Service and Networking Intelligence for Humanity
出版社Institute of Electrical and Electronics Engineers Inc.
ページ73-78
ページ数6
ISBN(電子版)9788995004388
DOI
出版ステータスPublished - 2020 9
イベント21st Asia-Pacific Network Operations and Management Symposium, APNOMS 2020 - Daegu, Korea, Republic of
継続期間: 2020 9 222020 9 25

出版物シリーズ

名前APNOMS 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
国/地域Korea, Republic of
CityDaegu
Period20/9/2220/9/25

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 情報システムおよび情報管理
  • 安全性、リスク、信頼性、品質管理

フィンガープリント

「Entropy-based IoT devices identification」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル