Bio-Inspired Multilevel Security Protocol for Data Aggregation and Routing in IoT WSNs

The resource limitation and unreliability of IoT WSN makes the sensors susceptible to a lot of malicious attacks. In this research work, we propose ANT Particle Swarm Optimization Adhoc On-demand Distance Vector (ANTPSOAODV) - a trust-based secure data aggregation method and an Energy-efficient Secure Routing protocol for a multi-hop environment. In the proposed protocol ANTPSOAODV, we achieve the purpose of secure data aggregation by detecting nodes' behaviour in the network, calculating the nodes' trust value and data gathering method. The proposed routing protocol has three important parts. First, the segmentation of IoT WSN into outer and inner zones based on the location of nodes. After this, in each zone, clusters are created based on the vicinity. Second, data transmission towards the sink from cluster heads represented as C.H.s in each zone is secured using a secret sharing scheme. Third, the analysis of data link for minimizing the routing disturbance. We analyze the performance of ANTPSOAODV in terms of Quality-of-Service parameters, i.e., end to end delay, throughput, packet delivery ratio, energy consumption, routing overhead, by varying; node mobility, number of sensor nodes, and input data rate. The obtained results have been compared with Ant Colony Based Secure Aggregation (ACBSA) and Polynomial Particle Swarm Optimization (POLY-PSO). The proposed protocol ANTPSOAODV outperforms other existing protocols in obtaining guaranteed QoS IoT WSNs holistically.