A Cognitive Digital Twin Architecture for Cybersecurity in IoT-Based Smart Homes

Cognitive Digital Twin (CDT) is an extension of Digital Twin with cognitive capabilities to monitor and analyse complex and unforeseen behaviours and to ensure critical reasoning and decision-making. Thus, CDT has a potential for enhancing cybersecurity for the Internet of Things (IoT)-based applications such as smart homes. In this paper, we developed a conceptual CDT architecture for improving cybersecurity in smart homes with dynamic threat detection and mitigation capabilities. The proposed approach applies closed feedback loops between cognitive process and cybersecurity using artificial intelligence and machine learning techniques. This will allow continuous monitoring of security-related information and analytics with complex behaviours within a virtual environment. The developed approach allows security testing and simulation in the virtual world for prediction and anticipation of dynamic security threats. It also facilitates dynamic updates to the physical world of attack prevention strategies for the dynamic optimization of smart homes security. Finally, this paper discusses the applicability of the developed CDT architecture in other IoT-based critical sectors.