Secure Cluster Head Selection and Routing in IoT-WSN Using Logarithmic Helix Spiral Search strategy with Orca Predation Algorithm

Internet of Things (IoT) is an extension of the Internet via a network with both homogeneous and heterogeneous devices including smart devices, consumer electronics, and Wireless Sensor Network (WSN) sensor nodes.However, the existing Cluster Head (CH) selection and routing techniques utilized for secure data transmission in IoT-WSNs are vulnerable to malicious attacks due to their inability to adapt to dynamic network conditions, as well as node-compromising issues.In order to overcome these limitations, a Logarithmic Helix Spiral search strategy with Orca Predation Algorithm (LHS-OPA) is proposed to enhance the adaptability of dynamic network topologies and prevent the node from compromising.The proposed OPA model with the encircling phase explores broadly and selects an optimal CH to avoid the node from compromising to malicious attacks.The LHS strategy identifies new attack patterns and adapts to the dynamic network conditions by expanding and contracting the spiral structures that enhance path selection for secure data transmission.The experimental results of the proposed LHS-OPA model are as follows: energy consumption of 10 J and 39 J for 1000 and 4000 rounds, respectively, thereby demanding lesser resources than the existing Chicken Swarm Optimization (CSO) approach.