A Comprehensive Investigation on Trust - Based Secured Routing System in Internet of Things Using Machine Learning Techniques

R. Elango, Dr. D. Maruthanayagam

Abstract: This analysis presents a comprehensive examination of trust - based secured routing systems in the context of the Internet of Things (IoT), augmented with machine learning techniques. Secure routing is a critical aspect of IoT networks, where trust mechanisms play a vital role in mitigating security threats. By integrating machine learning, the system enhances its ability to detect anomalies and adapt to evolving threats. The paper is present comprehensive investigation on trust models, routing protocols and machine learning applications in IoT security. It delves into the design principles of trust - based secured routing systems, exploring the integration of machine learning for improved security. Through case studies and analysis, the analysis highlights the efficacy of trust - based routing and machine learning in securing IoT networks. Finally, it discusses challenges, future directions, and the significance of trust - based routing in advancing IoT security.

Keywords: Internet of Things (IoT), secure routing, trust - based mechanisms, machine learning, security, anomaly detection and routing protocols