A Game-Theoretic Approach to the Early Detection of Internet of Things-Based Threats in Smart Home Automation

In the recent past, there has been rapid development in the Internet of Things (loT) technologies and related applications. As a new paradigm for connecting device machines, loT intends to incorporate the physical world more directly into digital processes. However, with such an innovative technology comes security threats that compromise the system's availability. The study proposed an early detection of loT -based security threats in smart home automation using a game theoretical approach. To assist with early detection, both pure and mixed game theory approaches were employed in an effort to compare how well each one performed with regards to response time. The algorithms and the experimental setup were developed in order to achieve our objective. The results of comparing the early detection of threats to security in loT using pure and mixed game theory strategies have showed that the system performs better with pure game theory than with mixed game theory. The comparison was conducted utilizing alternative evaluated methodologies that employed various strategies. The adoption of a game theoretical approach has demonstrated its efficacy in addressing timely detection challenges in broad system security environments.