[This article belongs to Volume - 55, Issue - 01]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-06-01-2023-484

Title : An approach to improve the performance of the machine learning algorithm with reduced dimension on UNSWNB15 dataset
kavitha.G, Dr.Elango N.M.,

Abstract : The development and utilization of internet-based technology has developed rapidly and also, we have been infused in an era of interconnections with the security that are delivered with the use internet technology in our day-to-day life services and these interconnections will lead to make networking is a most important aspect which also becomes as on indispensable part of our modern life. Due to the use of this technology has been creating us lots of security problems that are caused by malicious network intrusions. Therefore, securing device and system against malicious attacks has become an important and urgent task, since this intrusion can result in great risks. In this paper, we focus on the efficiency of PCA for intrusion detection to determine the advantages of use dimensionality reduction technique which improves the detection rate of the anomalies in the network data. The result is represented the various classification algorithm on Unswnb15 dataset of 4 9features. The result also presents the comparison analysis with and without PCA analysis on various classification algorithm.