Naive Bayes Augmented with Genetic Algorithm: Feature Reduction Approach for Effective Cyber Attack Detection
Canan Batur Şahin, Hayriye Tanyıldız, Özlem Batur Dinler · NATURENGS MTU Journal of Engineering and Natural Sciences Malatya Turgut Ozal University · 2023
This study examines the application of a Naive Bayes approach augmented with a genetic algorithm for the purpose of cyber intrusion detection. Being able to quickly adapt to the complex and variable nature of cyber-attacks, this approach offers an innovative solution, especially in feature reduction and data classification. The genetic algorithm is employed to identify the most optimal characteristics from the data sets, while the Naive Bayes classifier is utilised to detect cyber-attacks based on these features. Empirical examinations and evaluations have demonstrated that this comprehensive methodology yields superior precision rates and reduced rates of false positives compared to conventional techniques for detecting cyber intrusions. The findings of this study underscore the necessity of creating more efficient and adaptable measures in the realm of cyber security, particularly in light of the constantly evolving and unpredictable nature of threats.