Energy-efficient trust-aware secured neuro-fuzzy clustering with sparrow search optimization in wireless sensor network

Wireless sensor networks (WSNs) are a distributed collection of sensor nodes which are distributed geographically in the deployed environment to sense the natural phenomena. The sensed data are transmitted by the nodes using multi-hop communication until it reaches to the base station. Due to its resource-constraint nature of device and its communication in open and unfriendly environment, providing energy optimization along with the secured communication is a major challenge. In this work, a trust-aware neuro-fuzzy-based clustering along with sparrow search optimization algorithm (NF-SSOA) is proposed to provide energy-efficient trust-aware cluster-based secured data transmission in WSNs. The proposed protocol performs effective clustering of the nodes by employing neuro-fuzzy clustering algorithm, and routing is performed by sparrow search optimization algorithm. ECC-based digital signature algorithm is used in the proposed system to provide an efficient lightweight key generation, encryption, decryption, signature generation, and verification and to ensure hop-to-hop authentication of the nodes in WSNs. Moreover, the proposed protocol employs pseudo-random identity generation for performing anonymous authentication during data transmission in the network. The proposed protocol is implemented by using NS3 simulator. The simulation results prove that the proposed protocol improves energy consumption analysis, throughput, network delay, network lifetime, and packet delivery ratio when it is compared with other existing protocols. Moreover, the proposed protocol shows significant potential for resistance to various security and improves the quality of services in the network.