<![CDATA[The Internet of Things (IoT) has transformed modern digital infrastructure by enabling intelligent connectivity among billions of devices across industries, healthcare, transportation, and smart homes. However, the rapid expansion of IoT networks has introduced serious security challenges, including weak authentication, unauthorized access, data interception, and limited device resources. This study proposes a comprehensive IoT security framework that integrates mathematical modeling, lightweight encryption, artificial intelligence, and Zero Trust Architecture (ZTA). Graph theory is applied to analyze trust propagation and identify vulnerable nodes within IoT networks, while dynamic trust scores are used to improve authentication and anomaly detection. Simulation results from a 25-node IoT environment demonstrate that the proposed integrated model achieves higher trust accuracy and detection rates with low computational overhead compared to traditional security approaches. The findings indicate that combining mathematical optimization with Zero Trust principles provides an adaptive, scalable, and efficient solution for strengthening IoT cybersecurity in modern interconnected systems]]>
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