Lightweight Cryptography Based Secured Data Transmission Model for Quality of Service in Internet of Things-A Comparative Analysis

Abstract

Emerging technology like Internet of Things (IoT) seeks to facilitate the linking of numerous smart devices and diverse networks. IoT enabled platform architecture heavily relies on ad hoc networks because of their efficient, adaptable, low-cost, and dynamic infrastructures. To keep Quality of Service (QoS) intact in a multi-hop transmission, these networks make good use of the resources that are available. Secure and trustworthy data transmission is crucial because malevolent relay nodes can occur in multi-hop communication. Quality of service is considered in the suggested secure communication approach for networks based on the IoT that uses a trusted route model. Routing and security are the two most important components of a wireless network. With massive networks like the Internet of Things, these instances become two times as important. The novel nature of the IoT makes its far-reaching repercussions on healthcare stand out, yet it has had an influence on many aspects of society. When coupled with mobile computing, the IoT becomes even more beneficial due to mobile computing's characteristics. The beneficial impacts of the Internet of Things on healthcare are mostly attributable to mobile health, which is enabled by mobile computing. Wearables flood Internet of Things devices with data from their many sensors, actuators, and transceivers. Data on the IoT is vulnerable to a plethora of threats, assaults, and vulnerabilities. Consequently, a strong security solution is required to resolve concerns regarding the privacy, security, and vulnerabilities of the Internet of Things. This research presents an efficient routing protocol-based architecture for the secure and scalable transfer of healthcare data in the IoT. The presence of malicious nodes makes this network vulnerable to numerous attacks. This research presents a brief comparative analysis on the proposed routing model, group key management model and malicious nodes detection model in which these models are compared with the traditional models. The comparative analysis showed that the proposed models are efficient and effective in providing Denial of Service (DoS).