Fog Layer-based DDoS attack Detection Approach for Internet-of-Things (IoTs) devices

Akshat Gaurav, B. B. Gupta, Ching Hsien Hsu, Shingo Yamaguchi, Kwok Tai Chui

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Citations (Scopus)

Abstract

The Internet of Things (IoT) represents the network of smart devices that are connected through the internet. The devices in the IoT network collect data from the physical world and transmit it to a cloud server. The decentralized nature of IoT made it vulnerable to many cyber attacks. The DDoS attack is one of the attacks among all the cyberattacks and it attacks the availability of the network. Due to DDoS attacks legitimate devices in the IoT network not able to transmit the information to the cloud server. In this paper, we propose a Fog layer-based DDoS attack detection method for IoT devices. The proposed approach uses clustering and entropy-based method to identify malicious nodes in the IoT network. We implement our proposed approach on ommnet++ simulator and efficiency is evaluated by statistical parameters like packet delivery ratio, throughput, precision.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Consumer Electronics, ICCE 2021
ISBN (Electronic)9781728197661
DOIs
Publication statusPublished - 10 Jan 2021
Event2021 IEEE International Conference on Consumer Electronics, ICCE 2021 - Las Vegas, United States
Duration: 10 Jan 202112 Jan 2021

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
Volume2021-January
ISSN (Print)0747-668X

Conference

Conference2021 IEEE International Conference on Consumer Electronics, ICCE 2021
Country/TerritoryUnited States
CityLas Vegas
Period10/01/2112/01/21

Keywords

  • Cloud computing
  • Clustering
  • Entropy calculation
  • Fog computing
  • IoT

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