Optimizing Security Performance: Leveraging Multiclass Algorithms and Dimensionality Reduction for Enhanced Accuracy
Hashlee Sajeev Nambiar, L Rangaiah, P K Praksha, C Vasanthakumar, J Suriya Prakash · 2024
It architecture is a highly interconnected field, and one of its most essential components is Intrusion Detection System (IDS). The efficiency of network intrusion detection systems for defensive measures is influenced by the speed of detection. This study’s experiments by using CIC-DDOS2019 dataflow to assess intrusion detection systems. DR is achieved using Principal component analysis (PCA) which Is a dimensionality reduction approach which is used to minimize the amount of features while maintaining critical information. These study results provide insight into the relative effectiveness of various approaches, which helps practitioners choose the best course of action for comparable tasks. The moto of this research is to identify the insights and performance in classification using different algorithms along with the DR algorithm for IDS. Here we used 6 different machine learning algorithms to identify the best accuracy using the dataset CIC-DDOS2019, where decision tree algorithm gave the best accuracy of 0.99984