Towards an IoT Community-Cluster Model for Burglar Intrusion Detection and Real-Time Reporting in Smart Homes

R. Singh, H. Al-Khateeb, Gabriela Ahmadi-Assalemi, G. Epiphaniou

Research output: Chapter in Book/Published conference outputChapter


The systematic integration of the Internet of Things (IoT) into the supply chain creates opportunities for automation in smart homes from concept to practice. Our research shows that residential burglary remains a problem. Despite the paradigm shift in ubiquitous computing, the maturity of the physical security controls integrating IoT in residential physical security measures such as burglar alarm systems within smart homes is weak. Sensors utilised by burglar alarm systems aided by IoT enable real-time reporting capabilities and facilitate process automation which can be innovatively employed to increase security resilience and improve response to a burglary in smart homes. We research key-related methods of proposed security of home alarm systems and introduce an IoT Burglar Intrusion Detection (I-BID) solution, a new privacy-preserving alarms system with multi-recipient real-time reporting of intrusion in smart homes. Our approach is demonstrated on a developed and tested prototype artefact. The experimental results reveal that the proposed technique reliably detects intrusion, achieves real-time reporting of a home intrusion to multiple recipients autonomously and simultaneously with a high degree of accuracy. The key strength of our technique is its scalability to a community-cluster model as a burglary security mechanism.
Original languageEnglish
Title of host publicationChallenges in the IoT and Smart Environments: A Practitioners' Guide to Security, Ethics and Criminal Threats
EditorsReza Montasari, Hamid Jahankhani, Haider Al-Khateeb
ISBN (Electronic)9783030871666
ISBN (Print)9783030871659
Publication statusPublished - 27 Nov 2021

Publication series

NameAdvanced Sciences and Technologies for Security Applications (ASTSA)
PublisherSpringer, Cham
ISSN (Print)1613-5113
ISSN (Electronic)2363-9466


  • Internet of Things
  • Monitor
  • Detect
  • Alert
  • Police
  • Incident response
  • Intrusion
  • Senson
  • Smart home
  • Unauthorized access
  • Burglary


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