Trust-based Enhanced ACO Algorithm for Secure Routing in IoT

Abstract

The Internet of Things (IoT) is an expanding paradigm of object connectivity using a range of resource types and architectures to deliver ubiquitous and requested services. There are security issues associated with the proliferation of IoT-connected devices, allowing IoT applications to evolve. In order to provide an energy-efficient and secure routing method for sensors deployed within a dynamic IoT network, this paper presents a trust-aware enhanced ant colony optimization (ACO)-based routing algorithm, incorporating a lightweight trust evaluation model. As it is challenging to implement security in resource-constrained IoT networks, the presented model adopted bio-inspired approaches, offering an improved version of ACO towards secure data transmission cost-effectively while taking into consideration residual energy and the trust score of the sensor to be optimized. The trust evaluation system has been enhanced in the development of the proposed routing algorithm and the node trust value is evaluated, sensor node misbehavior is identified, and energy conservation is maximized. The performance evaluation is demonstrated utilizing MATLAB. In comparison to the standard bio-inspired algorithms and existing secure routing protocols, the proposed system reduces average energy consumption by nearly 50% regardless of the increase in the number of nodes and end-to-end delay of 40%, while finding the secure and optimal path in unison is designed to ensure trust in the IoT environment.