Awareness based gannet optimization for source location privacy preservation with multiple assets in wireless sensor networks

Abstract

The wireless sensor network (WSN) has been assimilated into modern society and is utilized in many crucial application domains, including animal monitoring, border surveillance, asset monitoring, and so forth. These technologies aid in protecting the place of the event's occurrence from the adversary. Maintaining privacy concerning the source location is challenging due to the sensor nodes' limitations and efficient routing strategies. Hence, this research introduces a novel source location privacy preservation using the awareness-based Gannet with random-Dijkstra's algorithm (AGO-RD). The network is initialized by splitting the hotspot and non-hotspot region optimally using the proposed awareness-based Gannet (AGO) algorithm. Here, the multi-objective fitness function is utilized to initialize the network based on factors like throughput, energy consumption, latency, and entropy. Then, the information is forwarded to the phantom node in the non-hotspot region to preserve the source location's privacy, which is far from the sink node. The proposed random-Dijkstra algorithm is utilized to route the information from the phantom node to the sink with more security. Analysis of the proposed AGO-RD-based source location privacy preservation technique in terms of delay, throughput, network lifetime, and energy consumption accomplished the values of 6.52 ms, 95.68%, 7109.9 rounds, and 0.000125 μJ.