HHOA_NCA – a Harris Hawk Optimization Algorithm (HHOA) on best possible Node Capture Attack (NCA) in Future WSN for Improving the Security of Ubiquitous Computing Intelligent System

Abstract

Abstract Wireless Sensor Network (WSN) is exceedingly predisposed to quite a lot of complex attacks due to confine resource deployment in big network communiqué vicinity. The adversary initiates a node capture attack to future WSN for snatching the private data from ubiquitous computing intelligent system through confiscating vertices (sensor nodes) for cooperating full network. We develop a Harris Hawk Optimization Algorithm for Node Capture Attack (HHOA_NCA) to identify the vertices in ubiquitous computing having higher seizing chance by attack over future network system. HHOA_NCA applies on function sensor node participation with multi objectives such as sensor node key contribution through links, sensor node contribution, sensor node energy cost, distance between sensor nodes and sensor node velocity. Key contribution is the number of keys utilized by vertices. The contribution of sensor nodes is evaluated as the association among all paths and vertices. Sensor node energy cost is obtained on the basis of energy expenditure for packet transmission through vertices over WSN. The distance between two sensor nodes is evaluated using neighbourhood degree. The velocity is measured by the stability time of a sensor node. Simulation is performed in MATLAB 2019a environment and experimental outcomes represent the greater performance of HHOA_NCA based on compromised traffic fraction, power utilization cost, attacking rounds and complexity over future WSN. The results of simulation for ubiquitous computing show that the HHOA_NCA obtains better results than MA, PCA, FGA, MREA, GA, ACO, PSO, FiRAO-PG and FFOA for single and multipath routing based on all performance factors over future network system.