DCBD: An Efficient Design of Dynamic Compromise Black Hole Attack Detection (DCBD) in WSN

In numerous fields, including environment monitoring, combat surveillance, and other uses, wireless sensor networks are widely employed. The data packets must be forwarded to the base station in each of these applications by a collaboration of the numerous sensor nodes. But it uses up the several capacities of a sensor node, including the battery, the storage, and the computational power. Using a technique called clustering, which groups sensors with similar characteristics under the control of a chosen sensor known as a Cluster Head (CH), wireless sensor networks (WSNs) can communicate more effectively. The Dynamic Compromise Black Hole Attack Detection (DCBD) algorithm is a novel method that this paper introduces to improve the throughput and network longevity of WSNs. The sensor network is segmented into a fair clustering in DCBD. Additionally, the CH selection for each location is determined by the sensor's energy, the distance to neighbors, and the distance to the base station. The performance of DCBD and other techniques have been compared using simulation studies, and the findings show that DCBD meets the design goals in terms of throughput, latency, and packet delivery ratio.