A Novel Approach for Gender Prediction through Fingerprint Analysis using Fuzzy C-Means Algorithm and Artificial Neural Network

Abstract

Wireless Sensor Networks (WSN) is a group of Sensor Nodes (SNs) which are performed to intellect a normal singularity from an environment. The minimum resources and computational power of WSN creates vulnerable to number of security attacks. To addresses this problem, this paper proposes a Multi-objective Trust-aware Dynamic Weight Pelican Optimization Algorithm (M-TDWPOA)-based secure and energy aware multi-hop routing in WSN with the Base Station (BS). The proposed method comprises of two significant steps: Initially, dynamic energy-efficient Cluster Head (CH) selection by utilizing the multi-objective functions such as Distance between neighbor nodes, Distance between BS to CH, Energy, Centrality and Trust Threshold. Then, dynamic secure multi-hop routing is selected by the multi-objective functions such as Distance between BS to CH, Energy, Trust Threshold which is dynamically reducing the network overhead. Furthermore, a security aware multi-hop routing is employed through the different trust classes like direct, indirect, recent and authentication. The proposed M-TDWPOA approach is estimated with various performance metrics like alive nodes, dead nodes, energy consumption, Throughput and so on. The proposed M-TDWPOA achieves the minimum energy consumption of 0.4927J, 0.4851J, 0.4771J, 0.4693J and 0.4617J when compared to the existing methods like Fractional Artificial Lion (FAL).