Akademik Veri Yönetim Sistemi
ISARC 1. INTERNATIONAL BLACKSEA SCIENTIFIC RESEARCH AND INNOVATION CONGRESS, Trabzon, Türkiye, 23 - 24 Aralık 2023, cilt.1, sa.1, ss.1-4, (Tam Metin Bildiri)
This work employs various approaches, including particle swarm optimization, ant colony optimization and the firefly algorithm, to evaluate the suggested method. It also calculates and implements the attach error criteria. Various machine learning methods based on the ant colony optimization, particle swarm and firefly algorithm were applied and evaluated. Based on the findings, a highly effective method was suggested, yielding a accuracy of the attach detection of 98.34 for decision tree. While the suggested procedure is high accuracy than other methods. The whale optimization algorithm is employed in this paper to choose the DDoS dataset's finest characteristics. The NSL-KDD dataset is used to detect key aspects of network traffic and the dataset in order to identify attacks like DDoS or CrossFire. In this stage, the chosen features are routed to the three classifiers: SVM, DT, KNN, and naïve base algorithm.