Recently, the Wormhole Attack (WA) affects the Wireless Sensor Networks (WSN). So far, there are '2' solutions to trounce WA, that is, utilizing specialized hardware or capturing a specific pattern extra overhead over the network. Some prevailing solutions for detecting-WAneed special hardware or firmly synchronized clocks or longer processing time in addition to that some solutions can't even locate the WormHole (WH) and also have low security.This paper proposed an efficient WH detection as well as Optimal Path (OP) selection for safe Data Transmission (DT) in WSN. The proposed workencompasses a '2' phase: i) training, and ii) testing. Here, the WSN values are considered and chosen secure node utilizing the Fit Factor (FF). After selecting the secure nodes, the routes are discovered aimed at the optimal assortment of the optimal routes. Next, the gathered data is tested with a trained system in which feature reduction and classification are performed. Lastly, the MCSC securely transfers the non-attack data. The proposed method's outcomes are examined and weighed against the other prevailing techniques and the outcomesexhibited the proposed method's efficiency for attack detection along withdata security.
KeywordsWireless sensor network (WSN) • Fit factor • Weight and diversity based deer hunting optimization (WD 2 HO) • Missing value imputation based t-distributed stochastic neighbor embedding (MVI-t-DSNE) • Linear quadratic estimation based deep artificial neural network (LQE-DANN) • Modified Cramer-Shoup Cryptography (MCSC)