A Hybrid Deep Learning Framework for Intrusion Detection in Database Systems Using Brown-Bear Optimization and Tunicate Swarm Algorithm

Li Wang, Brij Bhooshan Gupta, Akshat Gaurav, Mu‐Yen Chen, Razaz Waheeb Attar, Varsha Arya, Shavi Bansal, Ahmed Alhomoud · Journal of Database Management · 2025

Protection of networks from changing cyberthreats depends critically on intrusion detection. This article presents a hybrid deep learning framework using a tunicate swarm algorithm and brown-bear optimization for intrusion detection. The Tunicate Swarm Algorithm (TSA) was utilized for hyperparameter tuning; the Brown-Bear Optimization Algorithm (BBOA) was employed for feature selection, therefore lowering the dataset from 41 to 25 features. After five epochs, the model tested on the NSL-KDD dataset achieves 98% accuracy. Comparative study using conventional models showed that the suggested framework improved accuracy and loss reduction, therefore stressing its possibilities to improve intrusion detection systems.

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