Generating IoT traffic: A Case Study on Anomaly Detection

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

The Internet of Things (IoT) is expected to count for a large part of the Internet traffic and its impact on the network is still widely unknown. It is therefore essential to study the IoT Traffic in order to characterize its properties and evaluate its performances. In this paper, we propose a novel IoT traffic generator called IoTTGen. We model the IoT traffic and we generate synthetic traffic for smart home and bio-medical IoT environments. We also extracted anomalous IoT traffic from a real dataset and study the IoT traffic properties by computing the entropy value of traffic parameters. Our generator succeeds in capturing the characteristics of the IoT traffic, which can be visually observed on Behavior Shape graphs. Our generator can also serve to describe the main IoT traffic properties and also to detect IoT traffic anomalies.

本文言語English
ホスト出版物のタイトル2020 IEEE International Symposium on Local and Metropolitan Area Networks, LANMAN 2020
出版社IEEE Computer Society
ISBN(電子版)9781728181547
DOI
出版ステータスPublished - 2020 7
イベント26th IEEE International Symposium on Local and Metropolitan Area Networks, LANMAN 2020 - Virtual, Online, United States
継続期間: 2020 7 132020 7 15

出版物シリーズ

名前IEEE Workshop on Local and Metropolitan Area Networks
2020-July
ISSN(印刷版)1944-0367
ISSN(電子版)1944-0375

Conference

Conference26th IEEE International Symposium on Local and Metropolitan Area Networks, LANMAN 2020
CountryUnited States
CityVirtual, Online
Period20/7/1320/7/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Electrical and Electronic Engineering
  • Communication

フィンガープリント 「Generating IoT traffic: A Case Study on Anomaly Detection」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