A Secure Energy Efficient IoT Based Fractional Correlated Bayesian Data Transmission in WSNs

Wireless sensor networks (WSNs) contribute significant advantages over conventional methods for diverse applications, including healthcare, surveillance, environmental monitoring, and so on. WSNs are combined with the Internet protocol to develop the Internet of things (IoT) for associating day-to-day life objects to the Internet. The IoT is an extensive collection of devices containing sensors associated together over wireless networks. With the swift growing of IoT over the past decade, security has been recognized as one of the issues to be addressed during data transmission between several sensors. In this study, a secure machine learning-based IoT system for WSN is developed. This is called rectangular rationale correlated Bayesian (RRCB) method in WSNs for secure IoT data transmissions. To facilitate energy-efficient data encryption, a method named rectangular rationale energy-efficient algorithm based on an efficient key generation mechanism is proposed. The proposed RRCB in WSNs with the Internet to develop a novel machine learning-based IoT system using correlated Bayesian secured method to ensure secure data transmission between several interconnected sensors spread over a long converge range. The developed IoT based system has a significant performance by satisfying all the requisite security essentials. The experimental results show that the proposed method consumes less energy in comparison with the state-of-the-art methods.