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

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.