Enhancing Network Security through Viper Optimization Algorithm with Deep Learning Assisted Network Security System in Biomedical records

Abstract

The protection of biomedical records in healthcare from cyber attacks is an important necessity for modern-day settings. Enhancing intrusion detection and classification for such critical systems, there exists a novel approach proposed for Viper Optimization Algorithm with Deep Learning-Assisted Security System (VOADL-NSS). The novel approach applies the VOA feature selection technique after normalization of input data for choosing the most relevant attributes. For effective classification, an advanced Focus Enhanced Dual-directional Long Short Term Memory (FD-LSTM)model is used and further optimized through the Monarch Butterfly Optimization (MBO)algorithm. Evaluation results of the VOADL-NSS system on benchmark dataset CICIDS 2017 showed better results regarding accuracy, precision, recall, and F1-score compared to previous models. Results show that the system provides appropriate protection of sensitive data like biomedical records in healthcare through state-of-art intrusion detection and classification features.