Malware and botnet prevention in smart building IoT devices using blockchain-enabled federated learning

Christopher Taylor*, Biju Issac, Nauman Aslam, Kay Rogage, Graham Kelly

*Corresponding author for this work

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

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Abstract

The project proposes an AI-driven framework to enhance malware and botnet detection in smart buildings, employing blockchain and federated learning. It aims to overcome the limitations of conventional security methods by introducing a more dynamic and intelligent detection system. The initiative seeks to improve IoT security, establishing new standards for protecting smart building infrastructures against evolving cyber threats. Through the integration of blockchain and federated learning, the project addresses data security and privacy challenges, ensuring robust detection capabilities across various IoT environments.
Original languageEnglish
Title of host publicationInternational Conference on AI and the Digital Economy (CADE 2024)
Place of PublicationStevenage
PublisherIET
Pages146-149
Number of pages4
ISBN (Electronic)9781837241842
DOIs
Publication statusPublished - 24 Jun 2024
EventInternational Conference on AI and the Digital Economy: CADE 2024: AI in Health, AI in Finance, AI in Service-Oriented Industries, Digital Public Infrastructure, Smart Mobility & Sustainability - Venice, Italy
Duration: 24 Jun 202426 Jun 2024
https://warwick.ac.uk/fac/sci/wmg/news-and-events/events/wmgevents/cade2024/

Conference

ConferenceInternational Conference on AI and the Digital Economy: CADE 2024
Country/TerritoryItaly
CityVenice
Period24/06/2426/06/24
Internet address

Keywords

  • IoT
  • Blockchain
  • Federated Learning
  • AI
  • Machine Learning

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