Bayesian Kriging Regressive Similarity Index Deep Highway Transfer Learning Network for Efficient Cyber Attack Detection in Wireless Networks - DHIVYA. R; DR. B. SRINIVASAN (Utilitas Mathematica, 2025)
Wireless Network has integrated sensing technology and wireless communication for gathering the sensed data. Security attacks have major concern in wireless sensor networks (WSNs). Many researchers carried out on efficient cyber attack detection in WSN. But, the attack detection accuracy was not improved and time complexity was not minimized by existing methods. To address these issues, Bayesian Kriging Regressive Similarity Index Deep Highway Transfer Learning Network (BKRSIDHTLN) Method is introduced to perform efficient cyber attack detection with high accuracy and minimum time. Deep transfer learning involves adapting a pre-trained highway network for attack detection. Deep Highway Network collects the number of data samples and their features as input. After that, the feature selection is performed using Bayesian Kriging Regression to select the more relevant features.