A trust aware secure ant colony optimization based routing algorithm for Internet of Things

With the rapid spread of Internet of Things (IoT) systems enhancing the development of IoT applications, the issue of designing a secure routing algorithm for IoT, including reasonable trust management, has attracted more and more research attention. The unique characteristics of IoT networks make them vulnerable to attacks due to the resource constrained nature of IoT and the complex distribution of the network. Moreover, the sensors deployed in these kinds of networks are also energy-constrained. It is a challenging task to implement security in IoT networks when the design consideration comprises light weighted security mechanisms and routing protocols due to the insight that security is pricy regarding memory, computational power, and CPU cycles. The adoption of bio-inspired approaches contributes to discovering the optimal path for IoT routing by modeling the cognitive behavior of insect colonies to attain security cost-effectively. For wireless sensor network (WSN) integrated dynamic IoT networks, this paper presents a trust-aware secure Ant colony optimization (ACO)-based routing algorithm to provide security while searching for an energy-efficient optimal routing path. Implemented in MATLAB, the assessment results of the proposed routing algorithm are benchmarked to demonstrate that it has minimized the average energy consumption by nearly 50% even as the number of nodes has increased compared to the existing standard and secure routing protocols