Shielding Smart Home IoT Devices against Adverse Effects of XSS using AI model

Pooja Chaudhary, B. B. Gupta, Kwok Tai Chui, Shingo Yamaguchi

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

2 Citations (Scopus)

Abstract

IoT is transforming the way of living through infiltrating into every domain comprising our home, society and human body. However, this embellishment of IoT brings multitude of security concerns such as cross site scripting (XSS) vulnerability that can cause severe damage to the victim. Thus, this paper is focused on defending the smart home IoT devices against the XSS attack. The proposed approach employs OS-ELM classifier to detect the XSS attack and then neutralizes the effects of the XSS attack vector to secure user's device. The experimental outcomes unveiled that our approach achieves the higher accuracy of 0.98 with low false positive rate.

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

  • AI classifier
  • IoT Networks
  • IoT security
  • Malicious attack vectors
  • OS-ELM model
  • Smart home
  • XSS attack

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